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Article Excerpt
Abstract
Recent events indicate that the Republic of ESTONIA is on the fast track for catching up with its Western European neighbors. However, the country's successful performance has not translated to improved economic conditions for all regions of Estonia. This paper examines the nature of this regional diversity as it relates to the labor market. A statistical analysis indicates that age, educational, and nationality distributions vary across regions, causing earnings to vary as well. Policy initiatives to change the nature of these distributions, either through migration or educational incentives in regions with low earnings, or social policy changes to enhance the well-being of those living in the low-earnings regions, may provide more opportunity for those left behind in the transition process. (JEL J31)
Introduction
Estonia has shown great success in its economic transition, following some struggle with the economic changes that occurred immediately after independence in 1991. Today, Estonia's inflation rates are considered reasonable when compared to other transitional economies [UNECE, 2000]. The successful move to a market economy is supported by evidence of Estonia's privatization of many of its previously state-run businesses and the growth of foreign direct investment [Eesti Pank, 1999]. The country's successful economic performance has been accomplished with the constraint of a balanced budget requirement and a currency board. Because of its growing reputation as a stable economy, Estonia is on the fast track for joining the European Union (EU). Due to its designated status by the EU, Estonia is a much stronger economic player than many of the other transitional economies. [European Union Background Memos, 1997; EU White Paper Preparation of the Associated Countries of central and Eastern Europe for Integration in to the Internal Market of the Union, 1997].
Despite the positive developments for the nation as a whole, economic success has not translated to an improved standard of living for all residents of Estonia. For a small nation, Estonia displays a great deal of diversity in economic and social outcomes. For example, the average income per capita in 1998 varies from a high of 2,531 Estonian kroon (EEK) in Tallinn to a low of 1,287 EEK in Polvamaa [Statistical Office of Estonia, 1998]. (1) Recent evidence also suggests that the youngest, oldest, least educated, and those in industries poorly suited for free markets and free trade do not reap the benefits of the transition [Wilder et al., 1998, pp. 80-2].
This paper examines which regional demographic factors underlie average earnings differences for heads of household by region. A focus on earnings is used in order to develop possible policy initiatives for the labor market in each region. In this way, scarce government dollars can be efficiently spent to achieve Estonia's goal of improved economic well-being for all of its citizens.
Methods and Data Description
There may be various markets within a nation. A nation may not be so homogenous as to say that a single market outcome results throughout the country. For example, regions may differ by natural resources, the skills and characteristics of the labor force, the nature of infrastructure, and other productivity enhancing endowments, as well as cultural or political identity.
High mobility between regions would diminish these regional differences. The mobility of firms, labor, and investment would ensure that opportunities for above-normal profit are eliminated, and therefore some equilibrium between regions would develop in terms of earnings, unemployment, and the returns to productivity enhancing characteristics. Still, regional differences remain an important part of understanding a nation, even one as small as Estonia. Ties to land and other property, tradition, and limited flexibility in housing and employment for some imply that regional differences are likely to be persistent.
Many studies of regional economics have focused on the characteristics of a region that are likely to attract a business (spatial theory) or a group of people (migration theory) [Nijkamp and Mills, 1986, p. 2]. For such studies, a dynamic model is typically employed. The focus of this study is slightly different. This paper provides a snapshot of the differences that exist among the regions of Estonia and suggests reasons why these differences may exist. Descriptive statistics are used to gain a better understanding of the regional demographic differences and regression analysis is used to disentangle the complex effects of firm and individual characteristics on the average level of earnings for each region.
To investigate regional differences in earnings, five regions of Estonia are studied: the north, northeast, central, west, and southern regions. Estonia's economic activity is different in the northern region relative to the other four regions. The north includes Tallinn, the capital of Estonia, which contains 40 percent of the national population, and contributes 59.1 percent of GDP per capita to the country [Regional Bureau of Statistics of Central Estonia, 1999]. Estonia is also known for its primary ores, located mainly in the northeastern region, and for its large timber and agricultural resources, which are located in the central and southern regions. However, these other regions tend to have smaller cities and less opportunity for capital accumulation when compared to the north.
The 1996 Household Income and Expenditure Survey (HIES) provides the data for the investigation. The Statistical Office of Estonia compiles the data from interviews of approximately 1,000 households per month. The HIES collects data on each household's consumption and expenditure patterns, and on each member's demographic and employment characteristics, earnings, and income. (2)
Several conditions and limitations to the data were considered. First, due to the survey methodology, weights were used to convert each observation to be representative of the Estonian population. When the Statistical Office of Estonia selects a household, each household member is surveyed. The result is a bias toward including those in large families more frequently. The Estonian Statistical Office supplies a weight for each household to insure that the household observation represents the Estonian population. The household weight is then modified by household size to create a weight for individuals, which is ultimately used in the analysis.
The sample for descriptive analysis is limited to those heads of household over the age of 16 with full information, yielding an unweighted sample size of 10,224 and a weighted sample of 1,230,894. The...
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