Alternative Data for the Dynamic Modelling of the East European Transformation1 (original) (raw)
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LAM modelling of East European economies: methodology, EU accession and privatisation
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Scientific Papers of Silesian University of Technology – Organization and Management Series, 2020
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Proxy Data and Income Estimates: The Economic Lag of Central and Eastern Europe
The Journal of Economic History, 1997
In his recent article in this JOURNAL David F. Good gave income estimates for 22 regions of the Habsburg Empire from 1870 to 1910 and for the successor-state territories.' The article is based on a proxy-data approach that was apparently invented by Wilfred Beckerman and Robert Bacon. It has been employed by several authors, including N. F. R. Crafts, who used it to estimate Austrian and Hungarian incomes as well as the incomes of other European states, and Good himself in an earlier article.2 In his latest article Good used data from 11 European countries to estimate the usefulness of three proxy variables for predicting income.3 These variables were the percentage of the labor force employed in the nonagricultural sectors, the crude death rate, and the number of letters posted per capita. The logarithms of these variables were used as the independent variables in a regression equation, with the logarithm of GDP per capita as the dependent variable. The regression coefficients were then used to estimate GDP per capita for the Habsburg monarchy on the regional level, whereby data for the independent variables from 22 regions of the Empire were employed. This note will demonstrate that the measures used by Good produced statistical artifacts in both the absolute level of incomes and the economic growth rates; Good's estimates suffer from biases caused by inappropriate functional specification and by the inappropriate application to backward regions of coefficients that were estimated for relatively advanced countries. Second, I show that even within the set of European countries, individual country effects alter or offset the impact of variables generally associated with income and thus severely restrict the value of those proxy variables for predicting income even in advanced economies. To begin with, I ascertain the robustness of Good's specification, changing his regression model superficially. Instead of employing the share of the nonagricultural sectors in the labor force in its logarithmic form as an independent variable, I use the logarithm of the share of agriculture in the labor force. The informational content thereby remains the same, since the percentages of the agricultural and the nonagricultural sectors add up by definition to 100 percent. The results are shown in Table 1. Equation 1 resummarizes Good's model; equation 2 gives the values of the alternative model.4 Inserting the data for the independent variables from the 22 regions of the Habsburg Empire in either of the two equations should yield the same estimate of GDP per capita, given the fact that the information provided by the independent variables and the basic structure of the model remain virtually unchanged. Actually, the results are significantly different, as is shown in Table 2. The regression coefficients estimated from equations 1 and 2 were used to calculate estimates for each of the 22 regions and for Imperial Austria, Imperial Hungary, and the Habsburg Empire. The
SSRN Electronic Journal, 2014
This paper presents a quarterly macro econometric model of the Kazakhstan. The main goal is to provide a stylized representation of the Kazakh economy in order to simulate the consequences of several economic policies viewed by the authorities as essential during the period of transition to a market economy. The policy simulation potential of the model is illustrated by five types of simulations: interest rate shocks, foreign direct investment shocks, world oil price shocks, foreign demand shocks and nominal wages shocks. These sets of simulations show the importance of foreign direct investments in terms of theirs global positive effect, as well as the demand effect of an increase in the wages. We also find that effect of the tight monetary policy in not ambiguous; we argue that in some cases it is not the most efficient policy instrument to sustain the economy.
Romanian Journal of Economic Forecasting, 2007
The accession of twelve Central and Eastern European countries (CEEC) to the European Union (in 2004 and 2007) has given rise to new challenges in evaluating the effects of integration, for both the old and the new member states. These issues can only be addressed in a consistent, economy-wide framework, given that the institutional and economic changes implied by the membership process produce numerous, dynamic and complex interactions between the economic agents and sectors. Applied general equilibrium offers such a framework. This paper reviews the existing computable general equilibrium (CGE) models for the Central and Eastern European EU member states. In the past, the CGE models have been considered by many not to be appropriate for the former centrally-planed economies on both practical and ideological grounds. For example, in the CGE models, consumers typically maximize their utility and producers maximize their profits, while the demand and supply of products are cleared in markets at flexible equilibrium prices. This makes the CGE models particularly suitable for modeling a market-driven economy. In contrast, input-output models have long been used in many of the centrally-planned economies to solve the "material balance" problem in quantitative planning. These fixed-price models proved to be more suitable to a system where the major policy instrument was direct quantitative control and in which the price system was not given an important role. Nevertheless, as pointed out by Kis, , two factors enlarged the usefulness of the CGE models for the centrally-planned economies:
SSRN Electronic Journal, 2000
After more than two decades of transition and integration, countries in Central and Eastern Europe (CEE) still exhibit income levels that are significantly lower than the European Union (EU) average. This paper examines convergence in per-capita GDP between CEE and the EU over the period 1990-2012 by employing a combination of parametric and nonparametric methods, which provide more detailed insights than previous studies. The results indicate that the first decade of transition has been marked by divergence from the EU benchmark. In contrast, CEE countries experienced strong convergence over the 2000s, even in the face of the global financial crisis. However, the distribution of relative income evolved from a unimodal to a multimodal one, revealing growing disparities within CEE. Human capital accumulation and progress in economic reforms are identified as the key determinants of convergence, while financial deepening and price instability had a negative effect, especially in the past decade.