Integration and Inequality: Lesson from the Accessions of Portugal and Spain to the EU by Juan F. Jimeno , Olga Cantó , Ana Rute , Mario Izquierdo , Carlos Farinha Rodrigues DOCUMENTO DE TRABAJO 2000-10

March, 2000

(*) We are grateful to Stephen Jenkins, Ana Revenga and Javier Ruiz-Castillo for comments on earlier versions of this paper. We acknowledge financial support from the World Bank and from the Risk and Poverty in Transition Research Project. The usual disclaimer applies.

* Universidad de Alcalá de Henares (Madrid), FEDEA and CEPR.

** Universidad de Vigo.

*** Universidade do Minho and NIMA.

FEDEA.

ISEG and CISEP.

Los Documentos de trabajo se distribuyen gratuitamente a las Universidades e Instituciones de Investigación que lo solicitan. No obstante están disponibles en texto completo a través de Internet: http://www.fedea.es/hojas/publicaciones.html#Documentos de Trabajo

These Working Documents are distributed free of charge to University Department and other Research Centres. They are also available through Internet: http://www.fedea.es/hojas/publicaciones.html#Documentos de Trabajo

INTEGRATION AND INEQUALITY: LESSONS FROM THE ACCESSIONS OF PORTUGAL AND SPAIN TO THE EU ....1 1. INTRODUCTION....3 2. SOME MACROECONOMIC FACTS....9 2.1. GDP PER CAPITA AND LABOR PRODUCTIVITY....9 2.2. UNEMPLOYMENT AND INFLATION....12 2.3. THE SECTORAL COMPOSITION OF EMPLOYMENT....14 2.4. THE SKILL UPGRADING OF THE LABOR FORCE....16 2.5. THE EXTERNAL SECTOR; TRADE AND FOREIGN DIRECT INVESTMENT....17 2.6. THE INCIDENCE OF EU FUNDS....23 2.6.1. Regional policies in Portugal....25 2.6.2. Regional policies in Spain....27 3. TRENDS IN INCOME INEQUALITY (1980-95)....32 3.1. HOUSEHOLD INCOME INEQUALITY....33 3.2. SOME DIMENSIONS OF INCOME INEQUALITY....38 4. WAGE INEQUALITY....41 4.1. THE WAGE STRUCTURE AND ITS RECENT CHANGES....42 4.2. INSTITUTIONAL FACTORS SHAPING THE WAGE STRUCTURE IN PORTUGAL AND IN SPAIN....47 5. INTERNATIONAL TRADE, WAGES, AND EMPLOYMENT....50 5.1. EMPLOYMENT AND WAGE SHARES BY SKILLS AND INDUSTRIES....50 5.2. SOME DETERMINANTS OF THE CHANGES IN EMPLOYMENT SHARES BY SKILLS....54 6. CONCLUDING REMARKS....59 APPENDIX 1. DATABASES ON WAGES IN PORTUGAL AND IN SPAIN....64 REFERENCES....68

1. INTRODUCTION.

International economic integration has institutional, political, economic and social implications, many of them with distributive consequences. In principle, there are three main reasons why the income and wage distributions of a given country may change after accession to a wider economic area:

- First, liberalization of goods and factor markets, modernization of the economy, technological upgrading, which usually precede integration, and international factor flows may change the returns to capital and the wage share. For instance, Foreign Direct Investment (FDI, hereafter) very often embodies technological transfers, and, hence, changes of the aggregate production function, which are then reflected on factor returns. Even without technological upgrading, and provided that the aggregate production function is not Cobb-Douglas, the capital and the wage share react to real interests rates, markups, etc, which are affected by integration.

- Secondly, there are the labor market effects of integration. It is well understood that trade flows may affect the sectoral and occupational composition of employment and wage premiums by skills and education, as countries exploit their comparative advantage in inter-industry trade (Heckscher-Ohlin) or engage in intra-industry trade. Although this is an intensively researched area, the empirical relevance of international trade at explaining the rise of wage inequality observed in most OECD countries (see Gottschalk and Smeeding, 1997), and even some lees developed countries, is still under discussion (see, for instance, Slaughter, 1998, and Wood, 1998). Not only but also FDI flows may change the relative demand of high-skill and low-skill workers by targeting certain industries or by foreign firms having a different skill composition of the labor force with respect to domestic firms (see Feenstra and Hanson, 1995).

- Finally, there is some evidence that governments use social policies to ease the distributive consequences of international economic integration. Rodrik (1998) shows that there is a positive correlation between an economy's exposure to world markets and the size of its government, which is robust to additional explanatory variables and strongest when terms of trade risk is highest. Also, labor market institutions (like unemployment benefits, wage determination mechanisms, job protection legislation) are changed to adjust to the new economic environment, very often with evident implications for wage and income inequality. Agell (1999) shows that there is a negative relationship between some indicators of labor market rigidities and openness, what he interprets as globalization increasing demand for social insurance.

Moreover, the changes in the income and wage distributions caused by integration may vary across regions of the acceding country. First, factor mobility is typically concentrated in certain areas (FDI tends to go to the richest regions, while migration flows are higher in regions closer to the borders). Secondly, the regional distribution of domestic firms may also change after integration (as documented by Hanson, 1998, for Mexico after NAFTA). Thirdly, some countries pursue regional policies in an attempt at reducing regional inequalities and, in some economic areas, notably in the EU, there are institutional arrangements to improve social cohesion among the member countries which basically amount to transfers to the lagging regions.

On the determinants of the wage share, see Bentolila and Saint Paul (1998). Blanchard (1997) provides an explanation of the recent evolution of the wage share in OECD countries.

In the economic literature there are three lines of research, somehow disconnected, addressing the determinants of inequality and the relevance of trade and economic integration among them. First, there are many studies documenting the evolution of inequality in different countries by exploiting microeconomic data on income and expenditure (see Gottschalk and Smeeding, 1997, and the references therein) and several papers using the inequality indexes constructed by these studies to search for the determinants of inequality across countries. Broadly speaking, the latter studies typically find that exports/imports and FDI flows do not help to explain across-countries differences in inequality (see, for instance, Mahler, Jesuit and Roscoe, 1997). Secondly, with regard to regional evolutions, there are the empirical macroeconomic studies on regional convergence which search for the driving forces of either GDP per capita or labor productivity at the regional level within a given country (see Barro and Sala-i-Martin, 1991, Sala-i-Martin, 1996). A few studies, notably Ben-David (1993), have tried to relate income convergence across countries and trade liberalization, finding that the former occurs at the timing of the latter. Finally, there is the massive literature on the sources of increasing inequality since the early 1980s in developed countries, which some studies have related to international trade (se, for instance, Leamer, 1993, 1998, and Wood, 1994) while others pinpoint biased technological progress (Davis and Haltiwanger, 1991, Bound and Johnson, 1992, Lawrence and Slaughter, 1993, Berman, Bound and Griliches, 1994). Within this approach, there are some specific studies on the experiences of some developing countries undergoing trade reforms (see, for instance, Hanson and Harrison, 1999, on Mexico, and Currie and Harrison, 1994, on Morocco). In most developing countries small responses of employment and wages are found after large trade reforms. This can be a consequence of stringent labor market regulations constraining employment and wage adjustments although, as pointed out by Harrison and Revenga (1995), output changes after trade reforms in these countries were also small and, hence, no significant wage an employment adjustments were needed.

It is somehow surprising that economic research on the consequences of economic integration has paid less attention to the European experience. In Europe there were middle-income countries which had trade reforms and became members of the EU at a later stage. In particular, Portugal and Spain joined the EU in January 1 , 1986, after transition from an autocratic political regime to democracy in the mid-seventies and some reshuffling of their economic and institutional structures in the second half of the 1970s and first half of the 1980s. The reforms required by accession to the EU were gradual, as a seven years transition period was agreed for dismantling of barriers to trade and labor mobility. Hence, since the beginning of the 1980s, were structural reforms in the Southern countries started in preparation for accession, until the early 1990s when the transition period ended, there are significant changes in the regulation of trade, capital mobility and the labor markets of the Iberian countries.

This paper focuses on the distributive consequences of these changes. The joint consideration of both Iberian countries provides a good natural experiment on the distributive consequences of economic integration and the implications of different policies to ease these consequences. The two Iberian countries were at a different development stage at the moment of accession (with PPP adjusted GDP per capita being at 53% and 70% of the EU average, for Portugal and Spain, respectively). Since the mid-1980s, both Portugal and Spain have had some catching-up with the rest of the EU, despite different macroeconomic outcomes. Whereas Portugal had high inflation and low unemployment throughout the 1980s, Spain achieved one-digit inflation rates in the early 1980s but have sustained unemployment rates in the 15%-25% range. Portugal and Spain also had different degrees of openness to international trade, being Portugal substantially more open than Spain at the moment of accession. After accession, both countries' trade flows have increased and concentrated mostly with the EU, so that their comparative advantage seems to be in products requiring low-skill or semi-skill labor. And regarding social policies, Portugal and Spain seemingly share many institutional features: most labor market institutions are apparently similar on paper (although, on practice they seem to have different implications –see Bover, García-Perea, and Portugal, 1998), and social expenditures increased in both countries since the early 1980s.

Despite the coincidence in the moment of accession to EU and other similarities commented above, inequality trends have been different in the two countries in the last two decades. Some studies using microeconomic household data have documented a substantial reduction of household income inequality both in Portugal and Spain throughout the 1980s (see Rodrigues, 1993, 1994, and Gouveia and Tavares, 1995, for Portugal, Ayala et al., 1993, Del Rio, Ruiz-Castillo and Sastre, 1998, Del Rio and Ruiz-Castillo, 1999a and 1999b, and Sastre, 1999, for Spain). However, during the first half of the nineties, household income inequality has risen in Portugal, while it has remained more or less constant in Spain. During the 1980s household income inequality decreased both in Portugal and Spain in spite of increasing labor income and wage inequality (see Cardoso, 1998 and Rodrigues, 1999, for Portugal; Revenga, 1991, for Spain). In this regard, it is important to notice the effects of several labor market reforms, especially the liberalization of fixed-term employment contracts in Spain, which have had very relevant consequences for wage inequality as it created a dual labor market. Finally, within each country, regional differences in labor productivity have also been falling, especially since the mid-1980s. EU transfers through Structural and Cohesion Funds and national-specific regional policies seem to explain a significant fraction of this regional convergence (see de la Fuente and Vives, 1995, for Spain), although regional differences in employment rates have increased (see Jimeno and Bentolila, 1998, for Spain) and regional convergence of GDP per capita has, if anything, occurred at a much lower pace.

Nevertheless, the coverage of unemployment benefits in Portugal was almost insignificant until the early 1990s, while in Spain it increased continuously throughout the 1980s. Also, despite similar wage determination procedures and similar trends in labor demand and labor supply, there are significant differences in the wage structure in both countries (see Cantó, Cardoso and Jimeno, 1998, and section 4 below).

Thus, the Portuguese and the Spanish experiences after accession to the EU provide a natural field in which to search for the determinants of the distributive implications of economic integration. Here we lay out the available microeconomic and macroeconomic evidence on the causes of changing inequalities in the Iberian countries. The report is in two parts: the first part (sections 2 and 3) describes the most relevant facts regarding macroeconomic evolutions and inequality trends in both countries. In Section 2 we briefly describe the macroeconomic performance of Portugal and Spain before and after accession to the EU by documenting the differences between the two countries in relevant variables for the subsequent analysis, such as the level of productivity, the employment structure, the degree of openness, trade patterns, FDI inflows, and the transfers received by means of the EU Structural Funds. In section 3 we report trends in income and wage inequality during the 1980-95 period and discuss the main factors behind these trends. The second part of the report (sections 4 and 5) analyzes the microeconomic evidence on wage and employment adjustments after accession to the EU in both Portugal and Spain. In section 4 we look at how individual and jobs characteristics are remunerated in both countries by estimating wage regressions with microeconomic data. In Portugal, where microeconomic data are available for different years, we also look at the changes in the remuneration of those characteristics between 1985 and 1995. In Section 5 we focus on the changes in employment and wage shares of different types of workers (classified by educational attainments and occupations) in different industries. First, we document the sectoral distribution of these changes and, secondly, we relate within-firm changes to some firms' characteristics like foreign and domestic ownership and the proportion of sales and inputs which are exported and imported. Finally, Section 6 concludes.

2. SOME MACROECONOMIC FACTS.

In this section we briefly document the macroeconomic performance of the Portuguese and the Spanish economies during the last four decades, with a special emphasis on the facts which may play a relevant role at shaping the income and wage distributions.

2.1.GDP per capita and labor productivity.

We first provide a brief characterization of economic growth in the Iberian countries in the 1960-96 period by describing the evolution of GDP per capita and labor productivity in relation to the EU average (in PPS units). As seen in Figure 1, regarding convergence of GDP per capita with the EU, three periods can be distinguished:

- Both Portugal and Spain were relatively backward economies in the sixties. At the beginning of this decade GDP per capita (in PPS units) were about 40% and, slightly above 55%, of the EU average, respectively. During the 1960-75 period, both economies experienced some catching up (higher in Portugal) to reach almost 60% and about 75%, respectively, of the EU average, in 1975.

- During the second half of the seventies and first half of the eighties, a period of economic crisis in the Iberian countries, catching-up in GDP per capita stopped in Portugal, at a level around 55% of the EU average, and even receded in Spain, to a lower 70% of the EU average.

- Since accession to the EU in 1986 and up to 1996, Portugal has improved his relative GDP per capita from about 53% to 63%, and Spain from about 70% to around 75%. Since 1996, both Portugal and Spain have had growth rate above the average of the EU.

Nevertheless, the evolution of GDP per capita conceals some important differences in the evolution of labor productivity (GDP per employee) and of employment rates. As seen in Figure 1, Spain shows very rapid catching-up in labor productivity in the 1960-86 period to remain at about 95% of the EU average after 1986. On the contrary, Portuguese convergence in labor productivity, which was faster in the sixties and seventies, has been almost non-existent in the last decade (GDP per employee has risen only from about 52% in 1986 to 55% in 1996). Obviously, the different patterns of convergence in GDP per capita and labor productivity arise from the evolution of employment rates (employment as a proportion of the working age population). In the EU15, employment rates remained more or less constant in the 1960-75 period, and then have fallen down by five percentage points in the last two decades (from around 65% in 1975 to about 60% in 1996). In Spain, the fall of the employment has been much more dramatic: from about 57.6% in 1975, to less than 45% in 1985 and to 47.2 in 1996. On the contrary, in Portugal the employment rate has remained more or less constant around the 1975 level: it was 66.4% in 1975 and 66% in 1996, after reaching a minimum of 63.5% in 1985.

Figure 1. GDP per capita and labor productivity. Portugal and Spain, 1960-96. Source: EUROSTAT, Statistical Appendix to European Economy.

The relationship between economic development and inequality is thought to be of an inverted U-shaped form. As economies embark in technological and structural changes, it is likely that the demand for capital and skills increases while the demand for unskilled labor decreases. Hence, at the early stages of economic development, there is positive relationship between economic development and inequality, which is reversed as economic growth proceeds (this is labeled as the Kuznets' hypothesis; see Higgins and Williamson, 1999, for a recent empirical analysis of this hypothesis). Not only economic reform but also political reforms may have affected inequality. Rodrik (1999) argues that there is a positive relationship between the wage share and the “degree of democracy” across regions. In fact, wage shares increased in both Portugal and Spain during the second half of the seventies after transition to democracy, to start decreasing in 1980 in Portugal, and since the mid-1980s in Spain.

2.2. Unemployment and inflation.

Figures 2a and 2b plot the evolution of unemployment and inflation rates in Portugal and Spain during the 1960-96 period. Unemployment rates increased in the two countries at the mid-1970s, immediately after the first oil shock and coinciding with political transition in both countries, and remained high until the mid-1980s. Some authors (see Boeri et al., 1998) have argued that accession to the EU contributed to increase unemployment, since the structural reforms that were needed as a prerequisite for accession had negative effects on employment. However, while unemployment in Portugal remained below 10% with cyclical fluctuations and no significant trend in the 1975-95 period, in Spain unemployment soared to reach almost 25 per cent and show, apart from cyclical fluctuations, a slightly increasing trend since the mid-1970s.

As for inflation, there are also stark differences between both countries. After the oil shock in the mid-1970s, Spain started the disinflation period in the late 1970s, although from a higher level and at a smaller pace than the core of the EU countries, while Portugal has reduced its inflation rate to the EU average only recently in the early 1990s. In Spain the reduction of inflation from 10% to the current figure below 2% took 15 years and was associated with a rise of 13 percentage points in unemployment, whilst in Portugal it was accomplished in only 5 years and with hardly any extra unemployment.

See Blanchard and Jimeno (1995) and Castillo, Dolado and Jimeno (1998) for discussions of the causes of the unemployment differential between both countries.

Figure 2b. Inflation rate (GDP deflator growth rate) Source: EUROSTAT, Statistical Appendix to European Economy.

Regarding the effects of unemployment and inflation on inequality, there are reasons to believe that the former is more relevant than the latter. In Southern European countries unemployment tends to be unevenly distributed, being higher among youths, women and lowskill workers. In this case, for a given country and across time, unemployment and income inequality are positively related. However, as for wage inequality, the effects may be the opposite: as the demand for high-skill workers increases and the demand for low-skill workers decreases, either the relative wage of the latter falls or the low-skilled unemployment rises. Therefore, across countries, there is a negative relationship between changes in unemployment and changes in wage inequality (documented, for instance, in Bertola, et al. 1999). As for inflation, its effects on inequality depends on the panoply of indexation provisions embedded in the tax system, in transfers, and in other contracts between different economic agents. There is however the presumption that people at the bottom tail of the income distribution are less perfectly hedged against inflation, so that inflation and income inequality are positively related.

2.3. The sectoral composition of employment.

Along with this evolution of unemployment, there have been significant changes in the sectoral composition of employment. In Portugal this composition diverges quite markedly from the EU average. However, the last decade has witnessed a rapid decline in agricultural employment and a sustained expansion in the service sector (see Table 1). Currently 12% of the labor force are employed in agriculture, 30% in industry and 58% in services in contrast to 1985 where the shares were 22%, 33% and 45%, respectively. Spain underwent intense employment reshuffling in the sixties and early seventies. The importance of the agricultural sector diminished in favor of industry, and more especially, in favor of construction and service activities. Later on, the relative loss of agriculture and industry was significant as the service sector expanded to account 52% of total employment in 1985. Whereas the reduction of the primary sector is comparable to that in Portugal, albeit starting from a much lower share, the fall in industrial activity can only be explained by a deep crisis in a number of sectors (steel, household equipment, shipbuilding) in which the Spanish authorities had bet heavily in the past and which were severely hurt by the rise of energy prices. The need to undertake a drastic restructuring came only after the second oil price crisis, during the early eighties, following the failure to modify the expansionary strategy pursued by the Spanish government in order to ease the political transition in the mid-seventies.

In 1997, in Portugal (Spain) male unemployment rates were 11% (33.1%), 5% (13.6%) and 6.4% (10.8%) for age groups 15-24, 25-54 and 55-64, respectively. Female unemployment rates were 18% (46.1%), 6.5% (25.4%) and 3.4% (12.7%) for age groups 15-24, 25-54 and 55-64, respectively. For unemployment differentials across skill levels in Europe, see Nickell and Bell (1995).

For Spain, Ruiz-Castillo, Ley e Izquierdo (1999) have computed the change of household-specific price indexes during the 1980-98 period and find that the growth of these indexes is positively correlated with income

There is, however, an important difference between Portugal and Spain in this regard. In Spain, the decrease in agriculture started in the 1960s and implied some flows from agricultural jobs to manufacturing. Then in the 1970s and 1980s, these flows continued but the lack of job creation in manufacturing and the insufficient job creation in the service sector, despite the large increase in public jobs, resulted in a huge increase in unemployment (see Dolado and Jimeno, 1997, Marimón and Zillibotti, 1998). In contrast, in Portugal, the largest flows from agriculture seem to have happened in the eighties and resulted in a large increase of the service sector.

Table 1. Sectoral composition of employment, 1980-96

Source: OECD, Labour Force Statistics.

levels, particularly after 1990. Hence, the increase of income inequality is understated by the use of an aggregate consumer price index.

Obviously, the employment structure has relevant consequences for income and wage inequality. As workers move from low-productive agriculture to high-productive manufacturing, inequality falls. On the contrary, de-industrialization results in higher inequality (Bluestone, 1990, Levy and Murnane, 1992). On the latter, there is also reverse causality: higher inequality provokes more demand for services and, hence, a higher share of the latter in GDP and employment, although in some countries (notably Scandinavian countries) high taxation and extensive provision of social services by the State result in very low levels of inequality together with a high weight of the service sector both in employment and GDP.

2.4. The skill upgrading of the labor force.

Portugal and Spain are still among the OECD countries with the lowest levels of human capital, despite the very intense educational and skill upgrading they have had in the last two decades. As seen in Table 2a, in 1995 only 31 percent of the Portuguese aged 25-64 years and 43 per cent of the Spaniards of the same age have completed at least upper secondary education. However, the Table also shows that the younger cohorts are much more educated than the older ones reflecting large changes in the educational composition of the labor force. Table 2b confirms this fact by showing the educational attainments of new school leavers among the population aged 16-29 years of age. Moreover, the gender difference in skill upgrading shows that it is the female population which have increased by most its educational level. On top of that, the participation rate of females has also increased notoriously in both countries (from 59.8 per cent in 1983 to 64.1 per cent in 1995, in Portugal, and from 34.7 per cent to 47.4 per cent, during the same period, in Spain).

In the case of Portugal and Spain this effect has been further reinforced by increasing subsidization of agriculture, mainly due to the accession to the EU's Common Agricultural Policy. For Spain during the 1980-90 period, Sastre (1999) finds that, although income inequality increased within the group of agricultural workers, their improvement in relative income and their declining weight in total population contributed to declining income inequality overall.

Table 2a. Educational attainments by age group, 1995

Source: OECD (1997). Columns (2) and (6) give the percentage of the population aged 25-64 who have completed at least upper secondary and university education, respectively. The other columns give the ratios between proportions for those 25-34 of age and those corresponding to the other age groups.

Table2b. Educational attainments of new schoolleavers among the population aged 16-29 years, 1996

Source: OECD(1997). The gender gap is defined as

The changes in the composition of the labor force by age, sex and educational attainments obviously have consequences for the income and wage distribution. In Section 4 we will estimate how the remuneration to personal characteristics have changed in the 1985-95 period, that is, from, immediately before to ten years after EU accession.

2.5. The external sector: Trade and Foreign Direct Investment.

The Portuguese economy has traditionally been more opened than the Spanish economy. Although country size is an important determinant of openness, in this case historical reasons are also to blame for part of the difference: Portugal was a founding member of the European Free Trade Association (EFTA) in the 1960s. On the contrary, it is not until accession to the EU and, more apparently, since the early 1990s after completion of the transition period for dismantling of barriers to trade and labor mobility specified by the accession treaties, that the Spanish economy increased substantially its trade shares, so that part of the differences in openness with respect to Portugal started to vanish.

The evolution of the ratio of total exports and imports to GDP is shown in Figure 3. For Portugal, this ratio increased from about 40% to almost 70% in the 1960-86 period, to remain fluctuating around this level afterwards. Spanish exports and imports increased from about 15% of GDP in 1960 to almost 40% in 1986, and then, again, from about 40% in the early nineties to around 45% in 1996. As for geographical patterns of trade of goods, there is an increasing concentration of exports and imports of the two countries to and from the EU. As shown by Figure 4, exports to the EU have more than doubled in the last decade, although the timing of the rise has been different: while Portuguese exports of goods to the EU increased mostly in second half of the eighties, it has not been until recently that the Spanish ones have risen significantly. As for imports of goods from the EU, a similar pattern arises: strong rise of the Portuguese imports in the second half of the eighties and of the Spanish ones since the early nineties.

Source: EUROSTAT, Statistical Appendix to European Economy.

Finally, concerning the evolution of intra-industry versus inter-industry trade, one should expect that, since the two countries had a larger labor intensity and a higher share of farming population than their trade partners (mainly the rest of EU countries), inter-industry trade would be predominant. However, this has not been the case in Portugal and Spain, where the intra-industry trade share in total trade has gone up by 10 and 14 percentage points, respectively, between 1986 and 1995 (see European Economy, 1996, no. 4). As regards specific sectors with a strong export orientation and, therefore subject to stronger specialization in each country (see Table 3), one should emphasize the role of textiles in

Portuguese manufacturing, which still contributes 30% of export earnings, whereas there are other sectors (like food and beverage and electrical engineering) where FDI flows have strengthened their comparative advantage. Spain, in turn, has intensified specialization in products of medium and low quality with strong or intermediate demand at the EU level. Thus, while food stuffs gradually lost ground, durable consumer goods (cars exported to the EU and capital goods to Latin-American countries) have seen a steep rise in importance. Overall, it seems that international trade should have increased the demand for low-skill and semi-skill products and, hence, contributed to lower wage inequality.

Table 3. Trade by types of products

Source: EUROSTAT, Yearbook '97.

As for FDI, traditional theories stress the role of the divergence of factor prices, transport costs and tariffs, together with ownership specific advantages, locational advantages and internalization opportunities in the case of multinational enterprises. According to these theories we should expect FDI flowing in a single direction from capital intensive/high wage countries towards labor intensive/low wage countries. In this case, another important factor affecting FDI is economic stability and the degree of stringency of the labor market legislation (see OECD, 1994, chapter 4). Moreover, high transport costs and low firm level fixed costs may induce two-way FDI that will displace trade and become more intensive as countries converge in factor prices. Thus, on the one hand economic integration will tend to decrease FDI as tariffs are reduced, trade increases and factor prices converge, and on the other hand will foster FDI if the determinants of two-way FDI are relevant.

First, as seen in Table 4, it should be noticed that the Iberian countries are low wage countries for EU standards (more so Portugal than Spain). However, since the early eighties, average hourly labor costs relative to the EU average have increased in Portugal and Spain, although these increases were reverted by a sequence of currency devaluation episodes in the early nineties. Arguably, the differences in average hourly labor costs reflect differences in productivity (so that human capital in the receiving country matters) and PPS which firms take into account when deciding on FDI. However, it can be also argued that for FDI differences in productivity and PPS across countries are not relevant as a large fraction of productivity is firm-specific (independent of location) and production is traded in international markets. In any case, on the labor cost front, Portugal, and Spain seem good candidates to receive FDI inflows both before and after accession to the EU.

Table 4. Average hourly labor costs (EU12 1990=100)

Source: EUROSTAT, Labour Costs Survey.

For Spain, 1984, International Labour Office, Yearbook of Labour Statistics, 1994.

The evolution of FDI inflows in these two countries is given in Figure 5. As seen in the Figure, FDI inflows significantly increased in the eighties (mostly in the second half of this decade) both in Portugal and Spain. This increase reflects an overall increase in FDI which have taken place across the world since the mid-eighties together with accession to the EU. The liberalization and structural reforms of the eighties and nineties, together with the implementation of more orthodox fiscal and monetary policies, surely contributed to the rise of FDI flows. However, the recent experience is not very encouraging in this regard. After the FDI boom of the second half of the eighties, FDI inflows to both Portugal and Spain have decreased to almost the low levels of the seventies and early eighties, and are much lower than the inflows that other low-wage/EU countries are receiving (i.e., Ireland).

Source: IMF, Balance of Payments Statistics.

An important aspect of FDI in regards to inequality is its regional distribution. Figure 5 plots FDI inflows to Spanish regions and regional GDP per capita during the 1986-96 period. As can be seen in the Figure, FDI inflows are heavily concentrated in the richest regions, so that between-regions inequality increases. FDI will have an even higher positive effect on inequality if, as it seems likely, FDI increases the demand for high-skilled workers and, therefore, within-region inequality.

Figure 6. Regional distribution of FDI inflows (Spain, 1986-96) GDP per capita (logs, average 1986-96)

A similar concentration of FDI inflows in richer regions also can be found in Portugal. As shown in Table 5, the Lisboan region and the North consistently receive around 90% of all FDI inflows. Table 5. Regional distribution of FDI inflows (%), Portugal.

Source: Santos (1997: 151).

2.6. The incidence of EU Funds.

In the EU regional policies are high on the political agenda as a means to improve social cohesion among the member countries, and to foster economic development in the laggard regions. Thus, in addition to private FDI, since 1986 some member countries receive transfers from the EU's budget that are devoted to improve the infrastructure base and human capital resources. As seen in Table 6, EU Structural Funds currently amount to approximately

3% of GDP in Portugal and 1% in Spain, and have been increasing since the early 1990s. Also, Figure 7 shows that, in relation to total investment, these funds have represented a significant and increasing share of capital accumulation.

Table 6. Structural funds and cohesion funds receipts as percentage of GDP Source: Domenech, Maudes and Varela (1998).

Source: Domenech, Maudes and Varela (1998).

Regarding inequality, the most relevant aspect of EU Structural Funds is obviously their regional distribution. FDI inflows have a very characteristics regional concentration in the richest regions and therefore tend to increase between-regions inequality. Hence, international economic integration should be expected to increase regional differences in income and wages. To some extent, if regional policies are targeted to the poorest regions, they may counterbalance the regional effects of FDI inflows.

2.6.1. Regional policies in Portugal.

Until accession to the European Community, Portugal had no tradition of regional policy. Indeed, no budget line was specifically set for that purpose, no policy instruments were defined, and planning at the national level was basically dissociated from planning at the regional level – whereas the former was assigned to the Ministry of Finance and Planning, the latter was assigned to Commissions under the supervision of the Ministry of Internal Administration (see Pires, 1998, on which this section is based, for details on the evolution of the Portuguese regional policy). The foreseen accession to the EU led, in 1983, to changes in the structure of the Government, to accommodate for the first time a department specifically in charge of the coordination of the regional policy, which should implement in Portugal the distribution of the Community regional funds. In 1984 and 1985, the goals, the strategy, the instruments and the resources for regional policy in Portugal were first laid out, together with a statement of the interactions between regional goals and the other government policies. However, by 1986 the regional modulation of the Portuguese policy was still judged as insufficient by the European Commission, and a transition period was therefore defined. It was only in 1988 that a definite set of national rules for the distribution of the EU regional funding was approved at the Community level.

Table 7. Regional distribution of Regional Funds, Portugal.

Source: Pires (1998: 50).

The regional policy in Portugal was therefore set with the integration in the European Community in the background, and it has since accession been implemented in the framework of the EU regional policy. Table 7 reports the regional partition of the EU Funds in Portugal, between 1986 and 1988. Lisbon and the Northern region shared the lowest per-capita Regional Funds, revealing the regional concerns in the splitting of this type of subsidies. During the preparation of the Regional Development Plan for 1988-93, the conflict between competitiveness goals and regional equity goals was apparent (Pires, 1998: 93). The regional partition of the Regional Funds in Portugal between 1989 and 1993, reveals less strong regional equity aims. When compared to the previous three-year period, the trend towards the concentration of the funding in the most developed region is noticeable. In fact, Lisbon and the Tagus Valley gathered of the Regional Funds for the period 1989-93. Such a situation is partly explained by the funds aimed at recovering the Setúbal region, a declining industrial area south of Lisbon, where subsidized FDI was prominent during this period. Between 1994 and 1996, the trend towards the concentration of a major share of the subsidies in the Lisbon region does not show signs of declining. Nevertheless, due to the amounts of funding channeled to Portugal after 1991, it can be claimed that European Union regional policies and their implementation in Portugal had a certain equalizing impact across regions.

Indeed, this type of funding cannot be dissociated from the convergence of regional per capita GDP that, though in a slight way, took place in Portugal after 1991. While from 1985 to 1990 the regional dispersion of per-capita GDP increased, between 1990 and 1993 it showed signs of a slight decline (see Table 8).

Table 8. Coefficient of variation, regional GDP per capita, Portugal, 1985-1993

Source: Pires (1998: 59, 130). Note: Methodological changes implemented in 1991 by the National Statistical Office resulted in a break in this series.

2.6.2. Regional policies in Spain.

Spain had no regional policy of any sort until the late 1960s when incentives to private investment in lagged regions (mainly, Andalucia, Extremadura, Galicia, Castillas and Aragon) were put in place (see Mancha-Navarro y Cuadrado-Roura., 1996, for a detailed description). At that initial stage regional policies had a subsidiary character, resources devoted to them were scarce, and they followed the sectoral guidelines of industrial growth patterns of those years. Recently, since mid-1980s, regional policies begun to take an increasing importance as the political decentralization gained momentum. Furthermore, with the accession to the EU, given the requirements to achieve EU funding, formal Regional Development Plans (RDPs) have been implemented for the periods 1986-1989, 1989-1993 and 1994-99. The main objective of the RDPs is to reduce inter-regional inequality, supporting a sustainable growth pattern that lets to get the convergence with the EU average income per capita. They conceive three main instruments: i) investment in infrastructures, ii) capital transfers to accumulate social equipment in Health, Education and Housing, and iii) incentives to private productive activities. Thus, EU funding has been key for modern Spanish regional policies, resulting de facto in significant transfers to the regions with the lowest levels of GDP per capita (see Figure 8).

However, the regional concentration of FDI inflows has been even more intense, so that EU regional policies have not totally compensated for the lack of private investment in the poorest regions. In Figure 9 we plot the relationship between total foreign capital inflows (as percentage of regional GDP and average for the 1988-94 period) and regional GDP per capita. As can be seen in the Figure, some richest regions (Madrid, Navarra and Catalonia) have received total flows well above the rest. In the rest of regions, the differences in the contribution of foreign funds to capital accumulation have been much less noticeable, with the poorest regions (particularly, Extremadura) relying heavily on EU funding in this regard.

Figure 9. FDI and EU Funds in Spanish regions, (1988-94)

To what extent do FDI inflows result in widening regional differentials in labor productivity? To what extent have EU funds contributed to reduce these differentials? Under the assumption that capital goods are homogenous and, hence, regional production have the same elasticity with respect to all kind of investments, either private/public, or domestic/foreign, the relative impact of FDI inflows and EU funds on regional productivity differentials may be approximated by the contributions of both to capital accumulation. However, there is an additional reason why FDI inflows and EU funds can make a difference for the evolution of regional productivity. Being capital not homogenous, then it is likely that the elasticity of production with respect to capital accumulation is not invariant to the different kinds of investment. Thus, we proceed to perform regression analysis on the determinants of regional productivity (and regional GDP per capita) to assess the contribution that FDI inflows and EU funds, besides their direct contribution on capital accumulation.

For this analysis, we use a sample of 17 Spanish regions (corresponding to the NUTS2 level of EUROSTAT's regional classification) during the 1988-94 period (for which the regional disaggregation of FDI inflows is available). Following De la Fuente and Vives (1995) we postulate a constant return to scale with three types of capital private and public physical capital and human capital. We have data on the stock of each kind of capital in each region (although not distinguishing between domestic and foreign), on the proportion of employees who have at least completed secondary education (our proxy for human capital) and FDI inflows and EU Structural Funds (as proportions of regional GDP). Under the assumption that the domestic/foreign distinction is not relevant, the production function, in log-differenced form, becomes:

\[\Delta \left(y _ {i t} - l _ {i t}\right) = \alpha \Delta \left(k _ {i t} - l _ {i t}\right) + \beta \Delta \left(p _ {i t} - l _ {i t}\right) + \gamma \Delta h _ {i t} + \varepsilon_ {i t}\tag{2.1}\]

where y is (the logarithm of) production, l is employment, p is public physical capital, k is private physical capital, h is human capital, i denotes region, t denotes time, and is a random error term. For the estimation of the differential effects of FDI inflows and EU Structural Funds on regional productivity, we extend the previous specification as follows

\[\Delta (y _ {i t} - l _ {i t}) = \alpha_ {1} \Delta (k _ {i t} - l _ {i t}) + \beta_ {1} \Delta (p _ {i t} - l _ {i t}) + \gamma \Delta h _ {i t} + \alpha_ {2} F D I _ {i t} + \beta_ {2} E U S F _ {i t} + \alpha \varepsilon_ {i t}\tag{2.2}\]

where FDI and EUSF stands for FDI inflows and EU Structural Funds (both as a proportion of regional GDP), respectively. Under the assumption of constant returns to scale and perfect mobility of private capital, then the change in the private capital per employee can be eliminated from the equation (see De la Fuente and Vives, 1995), which is convenient since available regional data on private investment per employee are not completely reliable.

We estimate the simplified version of equation (2.2). The regressors are public capital per employee (in log-differences), the change in the proportion of employees with a least secondary education, the ratio of EU Structural Funds to regional GDP accumulated over the current and last two years, and FDI inflows as proportion of regional GDP also accumulated over the current and last two years. We accumulate these latter flows to take into account some likely delayed effects of both EU funds and FDI inflows on regional labor productivity. We estimate this specification in log-differences (in contrast to De la Fuente and Vives, 1995, who estimate a similar specification in levels and without considering separately the effects of EU Funds and FDI inflows). We use both OLS and IV estimators, to handle the endogeneity of EU Funds and FDI inflows. As instruments we use the (2 . order) lags of these two variables and the second-order lags of regional labor productivity and regional GDP per capita.

The results from the estimations are presented in Table 9. The simplest specifications (columns 1 to 4) estimated by OLS yield elasticities of production with respect to public capital between .14 and .31 (but which are statistically significant in tow out of the four cases). As for human capital, our proxy (the proportion of employees with at least secondary education) has mostly cross-regions variations and, hence, it is highly correlated with regional dummies which results in loss of statistical significance when regional dummies are included. Nevertheless, the point estimates of both elasticities in columns (3) and (4) are close to those estimated by De la Fuente and Vives (1995) using regressions specified in levels rather than in differences. In any case, our motivation was to analyze the differential impact of FDI inflows and EU Structural Funds on regional labor productivity. In this regard, we obtain some suggestive results. First, the OLS estimates indicate a negative differential impact of EU Structural Funds and a positive differential impact of FDI inflows –with respect to domestic public and private investment. However, while the former finding is not very robust –it disappears when IV are used for the estimation, see columns (7) to (9)-the latter finding still remains in one of the specification estimated by IV (see columns 9). Thus, overall, our results seem to suggest that the widening effects of FDI inflows on regional labor productivity arise form tow facts, the concentration of these flows on the richest regions and a positive differential impact with respect to other types of investment. On the contrary, although EU Structural Funds contribute very significantly to equalize the level of public capital across regions, their equalizing effects on regional labor productivity may be hindered by a lower elasticity of regional production per employee.

Table 9. Estimations of the effects of FDI inflows and EU Structural Funds on regional productivity and regional GDP per capita. Dependent variable: Regional labor productivity (in log-differences)

3. TRENDS IN INCOME INEQUALITY (1980-95).

In this section we document changes of income inequality in Portugal and Spain during the 1980-95 period. Following most studies on this topic, we use data from the Household Budgets Surveys (Encuesta de Presupuestos Familiares, EPF) conducted by the corresponding National Statistical Institutes at the beginning of the 1980s (1980-81), the beginning of the nineties, (1989-90, in Portugal, and 1990-91 in Spain), and the mid-1990s (1995 for both Portugal and Spain). In order to have a global overview of the changes in the income/expenditure distributions we use several indicators: the household distribution of total expenditure/income, the individual distribution of the per capita and per equivalent adult expenditure/income. The definition of income includes earnings, investment income, transfer and capital receipts, income in kind as production for home consumption and imputed rents, and it is net of income taxes and social security contributions. Households with negative incomes have been excluded. Making use of the consumer price index as a deflator, we report incomes and expenditures in 1990 prices. Unless otherwise stated, the OECD equivalence scale has been used to compute the equivalent income of each individual in the household. We compute both the Gini coefficient and the Theil index of the expenditure and income distributions, and exploit the properties of the Theil index to break down income inequality in within-groups and between-groups inequality. We also break down income inequality by sources of income.

3.1. Household income inequality.

Table 10 presents the main facts regarding household income inequality in Portugal and Spain during the 1980-95 period. For Portugal and regardless of the concepts of expenditure/income used, inequality fell down slightly during the 1980s, but increased during the first half of the 1990s. Rodrigues (1993) shows that the modest decline during the 1980s results in particular from the changes taking place at the bottom of the distribution, due to a much higher increase in the average living standards of those people at the bottom of the distribution. Taking equivalent income as reference, average real income grew by 24.8% between 1980 and 1990, 35.2% for the poorest 10% of the population; 24.4% for the richest 10% of the population, with the share of total income received by the bottom decile of the population rising from 3.1% to 3.4%. During the first half of the 1990s the trend is completely reversed: Between 1990 and 1995 average real income grew by 16.2% but the first decile of the population had an increase of equivalent income lower than 3.5%, contrasting with the tenth decile which registered an increase in average income of 29.1%. Hence, the income share of the first decile fell to 3%, below the corresponding figure for 1980.

The methodology and the variables covered by the surveys are very similar in both countries, so that comparisons of inequality indexes can be performed with some confidence. In Spain, for 1995, we can only use the longitudinal version of the survey (Encuesta Continua de Presupuestos Familiares, ECPF) which is not directly comparable to the cross-sectional version (EPF).

For the reasons to use expenditure as a measure of income, see Gouveia and Tavares (1995) and the references therein.

For Spain, where inequality was lower than in Portugal in 1980 (see the Lorenz curves for each country in Figure 10), the decrease of total income inequality took place during the whole 1980-95 period, although the trend during the first half of the nineties is somewhat blurred by the characteristics of the available data and the fact that inequality increases for some definitions of income. Thus, when the ECPF-longitudinal survey is used to compare 1990 and 1995, household inequality remains roughly constant, while inequality of income in either per capita or equivalent terms slightly increases. As in Portugal, the fall of inequality during the 1980s is mostly due to a much higher increase of incomes at the bottom of the distribution. For instance, for equivalent income, the 10 percentile increased by 42.9% between 1980 and 1990, while the corresponding rate of growth for the 90 percentile was 31.6%. Del Rio and Ruiz-Castillo (1999b) show that the fall in income inequality during this period results from both the reduction of inequality between different groups (defined according to age and household composition), arising from a relative improvement of the groups at the bottom of the distribution (and particularly, the group of retired and early retired workers), and the fall in within groups inequality (for most groups) together with a demographic change resulting in an increasing weight of middle and old age groups.

As already mentioned, EPF-1990 and ECPF-1995 are not comparable because of methodological differences between the two surveys. When using ECPF we are restricted to use a small sample of households observed during the four quarters of the corresponding year.

In contrast to total income, earnings inequality (measured by the distribution of total labor income, per capita labor income, and per adult equivalent labor income) did not show such a declining trend in neither of the two countries during the 1980s. In Portugal, increasing inequality in labor income, according to Household Budget Surveys, seems to be a more recent phenomenon of the first half of the nineties. However, other statistical sources suggest that labor income inequality was increasing even during the 1980s (see Cardoso, 1998). In Spain, the household distribution of labor income became more unequal during the 1980s and, especially, during the first half of the 1990s. In part, this is due to a concentration of employment in the households with higher labor income: the households in the upper half of the distribution not only have higher individual labor incomes but also more individuals receiving earnings. As for the individual distribution, the rise of inequality is mainly due to the increasing weight of groups with higher labor income dispersion (second-earners, youngsters) and to increasing within group inequality (see Sastre, 1999, chapter 2).

Thus, decreasing household income inequality in Spain between 1980 and 1995 contrasts with increasing household income inequality in Portugal. Moreover, it is noteworthy that, as for 1995, in Portugal the household distribution of total income is more unequal than the household distribution of labor income, while in Spain it happens the contrary. This suggests that other sources of income, mainly transfers, have been playing a very relevant role at shaping the income distribution in Spain and much less so in Portugal. Nevertheless, a detailed analysis of the contribution of different sources of income to overall inequality requires to breaking down inequality indexes in different relevant dimensions, as presented in the following section.

We will analyze the trends in wage inequality and their determinants with some detail in section 4.

Table 10. Income inequality in Portugal and Spain, 1980, 1990, 1995.

(*) It only includes households with labour income.

Figure 10. Lorenz curves. Portugal and Spain, 1980, 1990 and 1995.

3.2. Some dimensions of income inequality.

Here we focus on two important factors behind changing income inequality: i) the contribution to inequality of the different sources of income (labor earnings, self-employment, transfers, etc.), and ii) the contribution of regional differences to overall inequality, which is relevant since both Portugal and Spain have been subject to some reshuffling regarding the political power regional and local governments, and as seen in section 2.6) regional policies have been used intensively as means of redistributing income across regions.

As for the sources of income, we rely on Shorrocks (1982), who showed that, under certain restrictions, the proportional contribution of a factor income to total inequality would be invariant to the choice of inequality measure and would, for any inequality measure, be uniquely defined. By exploiting this result, Table 11 presents results concerning the decomposition of inequality by income sources in Spain and Portugal using I₂ (a General entropy measure suggested by Cowell and Kuga (1981) corresponding to half of the square of the coefficient of variation) as the inequality index. As seen in the Table, labor income is the most relevant component of income, and yields the highest contribution to overall income inequality. Moreover, the contribution of labor income to overall inequality rose from 43% to 49% in Portugal in the 1980-95 period and from 42% to 50% in Spain between 1980 and 1990 (using comparable data from the EPF) and fell from 56.6% to 52.9% in the 1990-95 period (using comparable data from the ECPF). Notice, however, that the share of transfers in total income and their weight at shaping the income distribution (contribution to inequality) is higher in Spain than in Portugal, which is consistent with the view that the Spanish government plays a more intense distributive role.

Table 11. Decomposition of inequality by income sources.

Additionally, following the procedure proposed by Jenkins (1995), changes in income inequality can also be broken down into income components: taking as the inequality index , then the change in aggregate inequality can be decomposed into an exact sum of changes in the contributions of the various factor components, which in turn depend on changes in correlations, factor shares, and factor inequalities (see Table 11). Table 12 shows the decomposition of the changes in income distribution by income sources in Spain and Portugal. These results suggest that there is a large influence of labor income inequality to the increase of total inequality in Portugal in the 1990s. In Spain, it is labor income and non-work private income the main sources of decreasing inequality both during the 1980s and the first half of the 1990s.

This is particularly relevant for Spain, where the decentralization of political power has been very intense since the transition to democracy in the mid-seventies. Spain is now in many regards, except on the formal side, a federal state where regional governments have competence in many economic issues.

I is a member of the General entropy measure suggested by Cowell and Kuga (1981), and corresponds to half of the square of the coefficient of variation.

Table 12. Decomposition of the changes in income inequality by income sources, 1980-1995 (%).

We now turn to the territorial dimension of inequality. As for inequality between-regions, Table 13 shows that territorial regional factors do not seem to play a very important role in the level of inequality both in Portugal and in Spain. The proportion of total inequality attributable to inequality “between-regional-groups” is not very significant (less than 3% in Portugal and around 7% in Spain), and its importance declines over the decade, particularly in Portugal. However, this perception on the little relevance of regional effects at explaining income inequality is somewhat misleading, though. Given the high degree of heterogeneity in the personal characteristics across individuals in the same region, it is not surprising that the contribution of regional differences to inequality is relatively low.

As Jenkins (1995) points out “there need not be a close association between factors with a large inequality

Table 13. Decomposition of overall inequality by territories.

4. WAGE INEQUALITY.

As seen in section 3, labor income inequality seems to have increased in both Portugal, during the first half of the 1990s, and Spain during the 1980-95 period. This is obviously the result of some changes in both the incidence and composition of non-employment and of wage inequality. In this section we focus on the main patterns of changing wage inequality in both countries. For this purpose we analyze the available microeconomic databases providing information on the wage distribution and individual and jobs' characteristics. First, from wage regressions we estimate how different individual and jobs' characteristics have been remunerated in the Portuguese and the Spanish labor markets. Secondly, we relate the observed differences in the wage structure of both countries to some specific labor market institutions. Appendix 1 contains a description of these databases together with the descriptive statistics of the samples used for the estimations of wage equations presented in this section.

contribution in a given year and the factors with the largest contributions to inequality change".

See section 2.3 for some comments on the incidence and composition of unemployment in both countries, and Bover, García-Perea, and Portugal (1998) for more details about the changing composition of unemployment in both countries.

4.1. The wage structure and its recent changes.

Here we aim at two goals. First, we consider changes in the Portuguese wage structure between 1985 and 1995 by running standards wage regressions for both years. This comparison will allow us to assess how the remuneration of observable individual and job characteristics has evolved. Secondly, we examine the Spanish wage structure for 1995 by means of similar wage regression on Spanish data. The comparison with Portugal will allow us to identify the main reasons for the different level of wage inequality in both countries .

Table 14 presents some wage inequality indicators for Portugal, 1985 and 1995, and Spain, 1995. As can be seen in the Table, wage inequality steadily increased in Portugal from 1985 to 1995, mostly because increasing dispersion at the right tail of the distribution, which confirms the findings in Section 3 from Household Expenditure Surveys data. For Spain, there is also some evidence of increasing wage inequality since the mid-1980s (not show in the Table). This evidence is based on the evolution of average wages of production and non-production workers and the fact that the share of fixed-term employees, who earn about 10% less than permanent employees (after conditioning for observable characteristics), increased from about 15% to 32% during the 1985-95 period. However, the increase of wage inequality in Spain has been smaller than in Portugal, and the comparison for 1995 reveals that the Spanish distribution is less compressed at the bottom and less disperse at the top than the Portuguese distribution. The main reasons for the different shapes of the wage distribution at the upper and bottom tails with respect to the Spanish are some features of the Portuguese minimum wage (which in relation to average earnings is higher –around .45- and applies to a higher proportion of workers) and the higher returns to education in Portugal (see below).

On this comparison, see also Cantó, Cardoso, and Jimeno (1998).

See Jimeno and Toharia (1993).

Table 14. Wage inequality in Portugal, 1985 and 1995.

Source: Computations based on MTS (1985, 1995) for Portugal, EES for Spain.

Both the Portuguese and the Spanish labor markets are characterized by sharp regional contrasts. In fact, in both countries, between-regions wage inequality is higher than between-regions total income inequality: In Portugal, regions accounted for 13.6% of overall earnings inequality in 1985 and 11.0% in 1995. Decomposing the Theil Index for Spain, we get a somewhat different picture. Regions accounted for only 6.6% of overall earnings inequality in Spain in 1995. This is around half less than what we found for Portugal. Unfortunately, the lack of individual data for the 1980's does not allow us to find out how regional evolutions have contributed to changing wage inequality in Spain.

Despite all of the above a better understanding of the evolution of the wage structure requires the estimation of wage regressions to estimate the remuneration of observable individual and job characteristics. The evolution of this remuneration across time can also provide some insights on the causes of changing wage inequality. Unfortunately, with available data, we only observe this evolution in Portugal.

The results of these wage regressions (see Table 15) lead us to highlight the following facts:

- The female wage gap Portugal has increased from 17% to 23%, as opposed to the trend in most other countries. Indeed, the average wage of women relative to that of men has remained stable, when evaluated in gross terms. However, as new cohorts enter the labor market, the qualification of women — evaluated as schooling, for instance — has improved at a faster pace than that of men. Therefore, the negative wage differential for female workers has been getting higher, once it is evaluated taking into due consideration the human capital of the worker. . As the qualification of female workers has thus been improving faster than that of men, especially as new cohorts enter the labor market, the rising gender wage gap could therefore result, probably as a transitory phenomenon, while the rising qualifications exhibited by women in the labor market are not matched by a comparable improvement in the type of occupations they reach and in the wage profiles that they face.

- Portuguese employers have been attaching less relevance to the human capital acquired in the workplace, as suggested by the decline in the returns to tenure, and the lower wage disadvantage imposed on newcomers into the firm. Instead, the returns to schooling increased between 1985 and 1995, especially during the second half of the 1980s (which can be observed from the results of a similar regression for 1991, not shown in the table). Another remarkable fact is the huge decrease of the relative wage of production workers (the corresponding coefficient goes from -.09 in 1985 to -.22 in 1995).

- Workers in the textile industry, which account for a high share of Portuguese exports, are subject to a strong wage disadvantage, after controlling for a wide set or worker and firm attributes (see the coefficient of the dummy variable for this industry, -0.11 in 1995). Thus, it seems that low-wages remain the basis for the Portuguese competitiveness in international markets. Nevertheless, it should be remarked that this negative wage differential remained more or less constant during the decade. In another major exporting industry -- machinery and transportation equipment industry -- the wage was slightly above the rest of manufacturing (coefficient for the dummy variable 0.01 in 1985), and increased during the decade. Also, the wage premium of mining workers increased over the decade. On the other extreme, the negative wage differential of hotel and restaurant workers became higher. In finance, but also in real estate and services to companies, and transportation and communications the large wage premiums of mid-eighties had declined sharply.

One should keep in mind that the female activity rate is very high in Portugal, unlike in the other Southern European countries, having increased from very low levels in the early 1960s. Several factors have contributed to this outcome. Massive male emigration and the colonial war in the 1960s, the Revolution in the 1970s, growing labor market flexibility in the 1980s and, throughout the period, low wages as the basis for international competitiveness, led to the integration of Portuguese women in the labor market, specially in traditional activities

- Larger firms pay higher wages, a situation that changed little during the 1985-95 period.

- Bargaining at intermediate levels – over firm type of agreements – yielded a wage premium that increased over the decade, relative to the centralized bargaining at the national or industrial level. By 1995, the wage premium associated with this type of bargaining was higher than the premium in firm-level agreements.

- Foreign firms pay higher wages (about 20%), although this wage premium has declined over the 1985-95 period. Thus, FDI flows have had a positive but decreasing contribution to wage inequality.

- Wages in the Northern region and in Lisbon, the largest employers, became further apart, once controls for a wide set of variables are included in the regression. In fact, the coefficient on the dummy variable for Lisbon increased from 0.08 in 1985 to 0.13 in 1995, relative to the reference category, the North. On the other hand, wages in the Algarve steadily increased with respect to the other regions, to reach in 1995 a premium similar to Lisbon.

and occupations and in the lower ranks of the qualification ladder. However, an additional motivation has more recently been impelling women to join the labor market — the growing investment in human capital.

Thus, increasing wage inequality in Portugal seems to arise mainly from changes taking place within industrial sectors rather than changes across industrial sectors. First, the inter-industrial wage structure has changed slightly between 1985 and 1995 with the fall in the wage premium of the finance sector being the most relevant fact in this regard. Secondly, the increasing returns to schooling and the huge decrease in the relative wage of production workers seem to be the main causes of increasing wage inequality in Portugal. Apart from education and skills, the labor market institutional features (like the impact of collective bargaining at the intermediate level) and regional factors (increasing wage premium in Lisbon and the Algarve) have also been relevant at shaping the wage distribution.

As for Spain, the lack of appropriate data does not allow to provide a detailed characterization of the trend of wage inequality and the changes of the remuneration of individual and job characteristics behind those trends. Some researchers, however, have documented some changes in the distribution of earnings (monthly or annual earnings without consideration of hours worked). For instance, Abadie (1997) finds that both returns to schooling and within groups dispersion decreased in a sample of male employees from the Household Budget Survey along the 1980s, San Segundo (1995) finds increasing returns to education during the 1980s in a sample of both males and females, and Sastre (1999) finds a decreasing gender gap in labor income, especially for people below 45 years of age.

There are many studies about the gender wage gap in Spain, but often using different surveys and methodologies at different years which cannot provide a robust conclusion about the changes in male-female wage differentials.

4.2. Institutional factors shaping the wage structure in Portugal and in Spain.

The second and third panel of Table 15 provide and illustrative characterization of the source of differences in wage inequality between Portugal and Spain. In particular, by comparison of the estimated coefficients of the variables included in the specification of the wage equations, the following conclusions arise:

- The female wage gap is slightly lower in Spain than in Portugal. As mentioned above, precise estimates on the evolution of the female wage gap in Spain are not available, although estimates from different cross-section samples at different years suggest that it has remained more or less stable, despite the fact that there has been an intense skill upgrading of the new cohorts of women relative to men (see Table 2b) which has resulted in increasing female employment rates but also a “downgrading” of the entry jobs in which wages are lower and less disperse (see Dolado, Felgueroso and Jimeno, 1999). In contrast, in Portugal the gender wage gap has increased as commented in the previous section.

- Returns to tenure are still significantly higher in Spain than in Portugal, in particular, given the sharp decrease observed in Portugal in late years. Also, the wage penalty to newcomers into the firm (less than one-year tenure workers), that has declined in Portugal, is still high in Spain. This is related to the high incidence of fixed-term employment contracts in Spain, who receive lower wages and have shorter job tenure that the employees with permanent contracts.

- Production workers wages are 11% lower than those of non-production workers, a similar level to that of the Portuguese blue-collars in the mid-1980s but around half of the current one. This lower gap between the wage of production and non-production workers in Spain can be explained by the compressing effects of trade unions intervention in wage determination, which results in binding bargained wages and higher unemployment for low-skill workers (see Dolado, Felgueroso, and Jimeno, 1997).

- Inter-industry wage differences are lower in Spain than in Portugal. As in the latter country, workers in the Finance Sector receive a wage premium above 30%. As for workers in transportation and communications, they are relatively better paid in Portugal. However, above all, the most interesting fact is the negative gap observed for Portuguese workers in the textiles industry and in Hotels and Restaurants, which is not present in Spain. Thus, it seems that in Portugal there are some low-wage, labor intensive industries where low-skill workers can still be employed. This is contrast with Spain where relatively high wages in these type of industries have resulted in high unemployment among low-skill workers.

- Finally, the regional differences in wages are much larger in Spain than in Portugal: Wages in Extremadura, Galicia and Murcia, for instance, are more than 20% lower than in Madrid. Interestingly enough, Extremadura and Galicia are the two Spanish regions geographically closest to Portugal.

Overall, institutional factors, like fixed-term employment in Spain and trade unions effectiveness at compressing the wage distribution, are key for the understanding of wage inequality in both countries. The incidence of the minimum wage in Portugal is the main reason for a compressed wage structure at the bottom tail, but higher returns to education (mainly due to still low relative supply of educated workers) results in high wage inequality for European standards. In Spain the main dimensions along which wage inequality is increased are returns to tenure (due to the incidence and characteristics of fixed-term employment) and the territory (due to large differences in wages among regions).

Table 15. Wage regressions.

5. INTERNATIONAL TRADE, WAGES, AND EMPLOYMENT.

In the previous section we have described the main changes in wage inequality observed in Portugal and Spain during the 1980-95 period. One interesting finding is that increasing wage inequality in Portugal seems to be driven mainly by increasing returns to education and falling relative wages of production workers. In Spain, where data are not available at the level of disaggregation needed to perform a similar analysis, the wage differences among industries and occupations are lower but the incidence of unemployment is especially higher for non-educated, low skill workers. This suggests the conventional explanation of the increasing demand for high-skill workers and falling demand for low-skill workers, which has been postulated to explain changing wage inequality in other countries. But in contrast with more developed countries, the trade patterns of Portugal and Spain seem to be conducive to increasing demand for semi-skill and low-skill workers and decreasing demand of high-skill workers. In this section, we document the changes of wage and employment shares of different types of workers according to their skills and industries. This will lead us to conjecture on the importance of trade regarding the recent evolution of wage inequality in both countries.

5.1. Employment and wage shares by skills and industries.

First, we look at changes in the employment and wage shares by sectors. For Portugal, we compute these changes with the data provided by MTS (see Appendix 1). For Spain, we have average wages and employment for different types of workers across firms from the 1988 and 1992 EUROSTAT Labour Cost Surveys (LCS). We group workers in four categories: high-skill, non-manual semi-skill, manual semi-skill, and non-skill. As a good approximation to the change in the relative demand of skills we take the change in the shares of employment and of the total wage bill for these categories of workers between 1988 and 1992. Tables 16a, for Portugal, and 16b, for Spain, report the results.

As seen in the table, the changes in wage and employment shares by skill and industries show different patterns in both countries. First, the wage share of high skill workers increases in both countries. However, while in Portugal it is concentrated in two sectors (Transports and Energy and Water) and did not take place in manufacturing, in Spain the wage share of high-skill workers increases by about 3 percentage points in all industries but the building sector. Overall, the industry dispersion of changes in the wage and employment shares of high skill workers is much higher in Portugal than in Spain. Secondly, in Portugal non-manual, semi-skill workers had decreasing wage and employment shares in almost all industries (the exceptions are the Building sector and the sector of Finance and services to companies), while in Spain this type of workers enjoyed increasing wage and employment shares in all industries but Trade and Restaurants. Finally, the changes of wage and employment shares of non-manual workers are reflected in the evolution of shares for manual and non-skill workers. Thus, in Portugal both manual semi-skill and non-skill workers had decreasing wage and employment shares in almost all industries, with the exceptions of Manufacturing and the Building sectors in the first case, and the Metal Industry, in the second. This is in contrast with the evolution in Spain where the fall of wage and employment shares among manual, semi-skill and non-skill workers is larger and more widespread across industries (with the only exception of Trade and Restaurants in the case of manual, semi-skill workers). Finally, it is noteworthy the differences in the changing composition of the labor force in Manufacturing: while in Portugal this sector did not seem to experience a very pronounced change in the relative labor demand by skills, in Spain it shows an increase in wage and employment shares of high-skill workers of roughly similar magnitude to the rest of the industries, and even higher than in the Service sectors.

The broad conclusion that emerges from these comparisons is that the nature of changes in the relative labor demand by skill seems to be different in the two countries. While in Portugal there is a clear industry bias in the changes of wage and employment shares by workers' skill, in Spain it seems to be a common phenomenon across all industries. The case of manufacturing, with an above-average skill upgrading in Spain and with roughly constant participation of manual workers in both the wage bill and total employment in Portugal, is very illustrative in this regard. Hence, it would be tempting to conclude that skill-biased technological progress is the main driving force behind changing relative labor demand in Spain, while in Portugal, international trade and specialization in specific manufacturing industries (textiles, etc) intensive in manual and low skill labor seem to be the cause for a lower decline in the relative demand of semi-skill and non-skill workers. This difference, together with the more compressed wage structure in Spain, may well explain why in Portugal wage inequality has been increasing with a roughly constant unemployment, while in Spain the rise of wage inequality seems to have been lower but the incidence of unemployment among semi-skill and non-skill workers is much higher. Nevertheless, this is a tentative conclusion that requires a closer scrutiny, which we perform in the following section as far as Spain is concerned.

Table 16a. Wage and employment shares by workers' skills and industries, Portugal 1988-92

Notes: Only full-time workers are included, and the monthly wage was considered (including the base wage, and other regularly paid subsidies). Top managers and professionals and personnel declared as highly skilled were coded as highly skilled; personnel declared as skilled or semi-skilled were included in the semi-skilled group; unskilled workers are a separate group in the original data set. Data: MTS, 1988, 1992.

Table 16b. Wage and employment shares by workers' skills and industries, Spain 1988-92

Notes: High-skilled workers include workers with a university degree and managers. Non-manual semi-skilled workers include assistants without a university degree, administrative officers, and auxiliary administrators. Manual semi-skilled workers include auxiliary personnel and production workers with some qualifications. Data: Labour Cost Survey, EUROSTAT (several years).

5.2. Some determinants of the changes in employment shares by skills.

For a better understanding of the driving forces of changing employment and wage shares we now turn to the analysis of within-firms changes. For Spain, a panel database containing information on a sample of manufacturing firms starting in 1990 (provided by the Encuesta de Estrategias Empresariales, EEE hereafter) provides some information on the composition of employment and wages by workers' occupations in each firm every four years. Thus, we can observe within-firms changes in employment and wage shares for the 1990-98 period, when the degree of openness of the Spanish economy experiences the highest increase (see section 2.5). We can group workers in four categories, depending on educational attainments (workers with and without a university degree) and on occupations (production and non-production workers).

The changes in employment shares in this sample is broadly consistent with those observed for the 1988-92 period with the EUROSTAT Labour Cost Survey. As shown in Table 17, we observe a significant increase in the employment shares of workers with university degrees of about 3.5 percentage points and a noticeable fall in the employment share of production workers, of about 2 percentage points, which are fairly similar across the industrial sectors included in the sample.

Table 17. Employment shares in manufacturing industries, Spain 1990-98.

Source: EEE.

Since the information on employment shares is available at the firm level, as it is information on some firms' characteristics, we can search for the determinants of within-firm changes of employment shares of workers with university degrees and production workers.

We start by running several specifications of the following OLS regression: where i stands for firms, is an industry dummies, is a vector of firms' characteristics and is a random error term. In the vector of firms' characteristics we include some measure of technological innovation (expenditures in R&D) the proportion of firms' sales being exported to foreign markets exports, the participation of foreign capital in the firm and some others. The results are in Table 18a, for workers with a university degree, and in Table 18b, for production workers.

As seen in the first four columns of Table 18a, the increase in the employment share of workers with university degree seems to be positively related to expenditures in R&D and the presence of foreign capital in firms' ownership, and negatively related to the ratio of exports to total sales. However, the statistical significance of these three variables is only marginal and decreases when either firms' size dummies or industrial dummies (or both) are included as regressors (see columns 5 to 7). In fact, besides industry affiliation and firm's size, we fail to find some other observable firm's characteristics helping to explain within-firms changes in the employment share of workers with a university degree. As for production workers, Table 18b shows that the fall in employment shares is general and is not related to any of the variables proxying firms' characteristics included as regressors. Finally, the industry affiliation dummies show no significant correlation with indexes of imports and exports ratio across industries which suggests that it is technology rather than international trade the main reason for the rise of skill labor demand.

Table 18a. Some determinants of changes in the employment share (%) Dependent variable: Change in the employment share of workers with a university degree, Spain 1990-98

Note: Standard errors in parenthesis. - (Metal minerals omitted).

Table 18b. Some determinants of changes in the employment share (%) Dependent variable: Change in the employment share of production workers, Spain 1990-98

Note: Standard errors in parenthesis. - (Metal minerals omitted).

6. CONCLUDING REMARKS.

This paper has collected some evidence on the trends in income and wage inequality in Portugal and Spain since the early 1980s. The most relevant facts which arise from this recollection are the following:

- Since the early 1980s the macroeconomic performance of both countries have been rather dissimilar with regard to convergence of income and GDP per capita with the EU, inflation and unemployment. Both countries share a changing composition of the employment structure (although from different starting levels and with a different timing), a large increase in the educational attainment of the labor force, a rise in the export and import ratios (traditionally much higher in Portugal) and a large incidence of FDI inflows during the second half of the 1980s. FDI inflows showed a marked regional concentration (towards the richest regions within each country) which has been partially compensated by EU transfers through the Community Structural Funds.

- In contrast with Portugal, where household income inequality fell down during the 1980s but increased in the first half of the nineties, in Spain income inequality fell down during the 1980s and did not increase as much as in Portugal during the first half of the nineties. The redistributive role played by transfers seems to be at the root of these different trends. In Spain, the tax reforms of the late seventies and the articulation of a Welfare State close to European standards, are the main reasons for decreasing household income inequality throughout the 1980s and first half of the 1990s. In Portugal, on the contrary, national redistributive policies seem to have been less relevant at shaping the income distribution than in Spain.

- Despite having labor markets with very different degree of flexibility and different wage structures, wage inequality has increased in both countries, more in Portugal than in Spain. In Portugal, both the returns to schooling and the gender wage gap increased between 1985 and 1995 while the relative wage of production workers and of some industries (most notably textiles) fell significantly over the same period. In Spain the wage structure is more compressed than in Portugal, which precluded a larger increase in wage inequality but resulted in a higher incidence of unemployment among low skill workers.

- The conventional explanation for increasing wage inequality relying upon decreasing demand of low-skill workers and increasing demand of high-skill workers seems also relevant for these two countries. However, while the rise of employment and wage shares of high-skill workers is general and of similar order of magnitude across all the sectors in Spain, in Portugal is concentrated in some specific sectors (like Transports and Energy and Water) and occurred to a much lesser extent in Manufacturing. Correspondingly, the fall of the employment and wage shares of manual, semi-skill and non-skill workers is much lower in Portuguese manufacturing, which may be related to the very strong export-orientation of some manufacturing sectors in this country.

- As for within-firm changes in the employment share of production workers, we have found a positive correlation between expenditures in R&D and the presence of foreign capital in firms' ownership, on the one hand, and changes in the employment share of workers with university degree, on the other. We also observe that these changes are negatively related to the ratio of exports to total sales of the firm. However, it seems that these changes are mostly determined by the firm's industry affiliation.

After the review of the available evidence, our interpretation of the distributive consequences of the Portuguese and Spanish accession to the EU is as follows. During the run-up and after the accession to the EU, both the Portuguese and the Spanish economy changed at a fast pace, undergoing modernization and some technological upgrading, being these changes limited to some sectors in Portugal, and fairly widespread in Spain. The impact of these changes was most noticeable in the labor market. In the "modern segments", the demand of skilled workers increased sharply. In Portugal the relative supply of highly educated workers increase at a lower rate and, therefore, rising wage premiums for certain worker attributes, in particular workers with university degrees, arose. In Spain, the relative supply of highly educated workers increased very rapidly (especially in the case of females since the mid-1980s ) and wage inequality did not increase as much as in Portugal. The more compressed wage structure in Spain translated less wage inequality into a higher incidence of unemployment among low skill workers. There is also a regional dimension in the process of modernization but EU regional policies and transfers seem to have contributed to reduce regional differences in labor productivity. However, given the low fraction of total inequality explained by between-regions inequality, and the divergence of employment rates (especially in Spain) the impact of EU policy instruments explicitly aimed at promoting social cohesion and the reduction of inequalities in GDP per capita has been relatively small.

As for the impact of international trade, while Portugal retained its traditional export specialization, with low-wages as the basis for international competitiveness, Spain shifted from traditional sectors to semi-skilled and high-skilled products, being its export composition closest to that of the other EU countries and engaging mostly in intra-industry trade, rather than inter-industry trade. Thus, in Portugal international trade contributed to sustain the wages and the employment shares of low-wage, low-skilled workers, driving part of the compression which took place at the bottom half of the wage distribution and generating low unemployment levels. Also some institutional arrangements, such as the minimum wage, and the action of collective bargaining, also contributed to such compression. However, this effect did not counterbalance the increasing wage premium for high-skilled workers resulting from modernization and technological upgrading and, as a result, wage inequality increased since the early 1980s. In Spain, demand of low-skilled workers decreased sharply because of technological changes and the reduction of traditional sectors, which combined with a fairly rigid labor market, resulted in high unemployment. Collective bargaining and other labor market institutions also contributed to increase wages at the bottom of the distribution and, hence, to increase unemployment of low-skilled workers. In the first half of the eighties, wage inequality was reduced because of the labor market institutional environment. Only since the mid-eighties, after the liberalization of fixed-term contracts, the increase in wage inequality is more noticeable, although the bottom tail of the wage distribution continues to be compressed by unemployment of the least productive workers.

See Dolado, Felgueroso and Jimeno (1999).

Finally, FDI inflows, being concentrated in the richest regions in both countries, had mostly an impact on the regional differences of labor productivity. However, FDI inflows have not been a very relevant part in the explanation of the within-regions trends in the earnings distribution, since FDI boomed during a short period of time, returning to relatively low levels afterwards and, more importantly, foreign companies slightly increased their employment share (from 6.9% in 1985, to 8.6% in 1995, in Portugal). Furthermore, the wage setting behavior of foreign firms in both countries has become increasingly close to national standards, as the wage premium associated with foreign companies decreased (from 0.24 to 0.18 in Portugal during the 1985-95 period, according to the coefficient of that dummy variable in wage regressions presented in section 4.1, while in Spain, as shown in section 5.2, the participation of foreign capital does not seem very relevant at explaining changes in the employment shares of high-skill and low-skill workers).

Thus, our interpretation of the Portuguese and Spanish experiences with international integration relies heavily on institutions. Government transfers seem very relevant to explain differences in the level and the trends in income inequality. Labor market institutions seem to explain the different responses of the wage structure and the incidence of unemployment to technological upgrading and international integration. Spain responded to reshuffling of economic activities and the implied uncertainty brought up by international integration by an increase in social expenditures and extensive regulation of the labor market, while Portugal relied upon more wage flexibility to accommodate the necessary adjustments. We have documented to some extent the tradeoffs which are to be taken into account when choosing between these two options.

Appendix 1. Databases on wages in Portugal and in Spain

In Portugal there is very detailed information on the wage structure since 1982. An extensive data set is gathered annually by the Ministry of Employment and Solidarity (Quadros de Pessoal -QP), based on a questionnaire that every establishment with wage earners is legally obliged to fill in. Reported data match the establishment (location, economic activity and employment), the firm (location, economic activity, employment, sales, legal setting) and each of the workers (gender, age, skill, occupation, schooling, tenure, earnings - split into base-wage, tenure-related earnings, other regular paid subsidies, irregular subsidies and overtime pay, duration of work - normal and overtime), as well as the mechanism of wage bargaining. By design, public administration and domestic work are not covered by the database (though state-owned companies are) and in practice neither is agriculture. For the remaining sectors, is a very reliable source of information, being in fact a census of firms, establishments, and their employees.

However, in Spain reliable microeconomic data on wages are available only for 1988 (when EUROSTAT Labour Costs Survey –LCS, was first conducted in this country), 1992 (the second Spanish wave of the LCS) and 1995 (Encuesta de Estructura Salarial -EES, conducted by the Spanish National Statistical Office). The latter collects detailed information on individual earnings as well as employers (economic activity, size, legal setting, type of wage bargaining) and workers' (gender, education, skill, occupation, tenure and, most importantly, monthly earnings) characteristics, information which is missing in the LCS. The EES sample is selected from the population of establishments with more than 10 dependent workers in a two-stage sampling method. The economic activity, region and size of the firm determine the first stage selection while the number of workers within each of the groups was chosen in a second stage. Our EES sample refers to 1995 and includes 14,636 establishments and 130,197 full-time workers between 16 and 65 years. For our measures of inequality we only consider full-time employees. To guarantee comparability of the Portuguese data with the available Spanish data set, we draw a sample from the QP following similar procedures as the Spanish National Statistical Office uses to choose the sample of the EES. Tables A.1.1. and A.1.2. present the main descriptive statistics of our Portuguese and Spanish samples of employees.

The sampling process involved two steps: a 75% random sample of firms was drawn, stratified according to industry (48 categories), region (5 categories) and firm size (5 categories); subsequently, workers within the firm were sampled. Five workers were selected from firms with 10-19 wage-earners; 25% of the wage earners were kept from firms with 20-49 wage earners; 17%, 13% and 10% workers were drawn from firms with 50-99, 100-199 and over 200 wage-earners, respectively.

Table A.1.1. Descriptive Statistics, Portugal 1985 and 1995

Education below the primary level was coded as 0. (2) The Portuguese Classification of Occupations in 1985 and 1991 was not strictly comparable to this one. (3) Agreements signed between one or several unions and one or several employers' associations, often covering an economic sector, were coded as national/industrial level bargaining.

Table A.1.2. Descriptive Statistics, Spain 1995

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RELACION DE DOCUMENTOS DE FEDEA

COLECCION RESUMENES

98-01: “Negociación colectiva, rentabilidad bursátil y estructura de capital en España”, Alejandro Inurrieta.

TEXTOS EXPRESS

99-02: “Economic implications of the demographic change in Spain: Call for research”, Namkee Ahn.

99-01: “Efectos macroeconómicos de la finalización de las ayudas comunitarias”, Simón Sosvilla-Rivero y José A. Herce.

DOCUMENTOS DE TRABAJO

2000-10: “Integration and Inequality: Lesson from the Accessions of Portugal and Spain to the EU”, Juan F. Jimeno, Olga Cantó, Ana Rute Cardoso, Mario Izquierdo y Carlos Farinha Rodríguez.

2000-09: “Explaining Youth Labor Market Problems in Spain: Crowding-Out, Institutions, or Technology Shifts”, Juan J. Dolado, Florentino Felgueroso y Juan F. Jimeno.

2000-08. “Distributional aspects of the quality change bias in the CPI: Evidence from Spain”, Javier Ruiz-Castillo, Eduardo Ley y Mario Izquierdo.

2000-07: “Testing chaotic dynamics via Lyapunov exponents”, Fernando Fernández-Rodríguez, Simón Sosvilla-Rivero y Julián Andrada-Félix.

2000-06: “Convergencia: Un análisis conjunto de los sectores. Aplicación al caso de las regiones española”, Pablo Álvarez de Toledo, Jaime Rojo, Álvaro Toribio y Carlos Usabiaga.

2000-05: “The Laspeyres bias in the Spanish consumer price index”. Javier Ruiz-Castillo, Eduardo Ley y Mario Izquierdo.

2000-04: “Evaluación de los efectos del Plan Prever a partir de un modelo de simulación de reemplazos del parque español de automóviles”, Omar Licandro y Antonio R. Sampayo.

2000-03: “Minimum consumption, transitional dynamics and the Kuznets curve”, María José Alvarez y Antonia Díaz.

2000-02: “Vintage human capital, demographic trends and endogenous growth”, Raouf Boucekkine, David de la Croix y Omar Licandro.

2000-01: “Vintage capital and the dynamics of the AK model”, Raouf Boucekkine, Omar Licandro, Luis A. Puch y Fernando del Río.

99-21: “Los efectos macroeconómicos de la Agenda 2000”, Simón Sosvilla-Rivero y José A. Herce.

99-20: “Unemployment duration and workers’ wage aspirations in Spain”, Namkee Ahn y J. Ignacio García-Pérez.

99-19: “El patrón inversor de los establecimientos industriales de la Comunidad de Madrid”, Ana Goicolea, Omar Licandro y Reyes Maroto.

99-18: “Crecimiento óptimo, depreciación endógena y subutilización del capital”, Omar Licandro, Luis A. Puch y J. Ramón Ruiz Tamarit.

99-17: “Panel data and tourism demand. The case of Tenerife”, F. J. Ledesma-Rodríguez, M. Navarro-Ibáñez y J. V. Pérez-Rodríguez.

99-16: “Redistribution in the Spanish pension system: An approach to its life time effects”, Joan Gil y Guillem López-Casasnovas.

99-15: “The plutocratic bias in the CPI: Evidence from Spain”, Javier Ruiz Castillo, Eduardo Ley y Mario Izquierdo.