Does Evidence on Regional Economic Convergence Depend on the Estimation Strategy? Outcomes from Analysis of a Set of NUTS2 EU Regions

Abstract

The regional economic convergence/divergence issue has been discussed extensively recently, but results obtained are not always interpretable unequivocally as a consequence of the different estimation strategies used. As it is widely recognized, the most common theoretical framework applied to measure the speed of economic convergence among countries or regions remains the β-convergence approach, linked to the neoclassical Solow model. There have been many attempts to consider variations of the basic cross-sectional specification ranging from panel data models to Bayesian spatial econometric techniques. The application of spatial econometric methodologies is an essential tool for proper statistical inference on regional data. In this context, the aim of this paper is to connect the different results obtained in the literature. More specifically, we address whether or not evidence on convergence depends upon the estimation strategy, by taking the same set of data and systematically comparing the results obtained from different estimation strategies. The results from a set of NUTS2 EU regions conclude that both the model implied by the cross-sectional analysis and the one referring to the space-time dynamics incorporated in the panel specification point to convergence. The concept of convergence implied is, however, quite different, as demonstrated throughout the paper.     

DOES ICT GENERATE ECONOMIC GROWTH? A META‐REGRESSION ANALYSIS

Despite phenomenal technological progress and exponential growth in computing power, economic growth remains comparative sluggish. In this paper, we investigate two core issues: (1) is there really no connection between ICT and national economic growth? and (2) what factors moderate the ICT–growth relationship? We apply meta‐regression analysis to 466 estimates drawn from 59 econometric studies that explore the Solow or Productivity Paradox that there is little impact of ICT on economic growth and productivity. We explore the differential impact of ICT on developed and developing countries and the differential impact of different types of ICT: landlines, cell phones, computer technology and Internet access. After accommodating potential econometric misspecification bias and publication selection bias, we detect evidence that ICT has indeed contributed positively to economic growth, at least on average. Both developed and developing countries benefit from landline and cell technologies, with cell technologies’ growth effect approximately twice as strong as landlines. However, developed countries gain significantly more from computing than do developing countries. In contrast, we find little evidence that the Internet has had a positive impact on growth.     

A two-stage model to forecast elections in new democracies

The purpose of this article is to propose a method to minimize the difference between electoral predictions and electoral results. It builds on findings that stem from established democracies, where most of the research has been carried out, but it focuses on filling the gap for developing nations, which have thus far been neglected by the literature. It proposes a two-stage model in which data are first collected, filtered and weighed according to biases, and then output using Bayesian algorithms and Markov chains. It tests the specification using data stemming from 11 Latin American countries. It shows that the model is remarkably accurate. In comparison to polls, not only does it produce more precise estimates for every election, but it also produces a more accurate forecast for nine out of every ten candidates. The article closes with a discussion on the limitations of the model and a proposal for future research.     

MEASUREMENT AND DETERMINANTS OF MULTI-FACTOR PRODUCTIVITY: A SURVEY OF LITERATURE

This paper surveys and synthesizes fast-growing literature on the measurement and determinants of multi-factor productivity (MFP). We identify three strands of the literature to measure MFP: the first is growth accounting, which decomposes observed economic growth into the contribution of factor inputs and technological change, called the Solow Residual; the second is index number methods, accompanied by frontier techniques; the third is growth regressions and econometric methods used to estimate productivity across countries and regions. We keep our focus on assessing the major strengths and weaknesses of commonly used methods for MFP measurement and categorize existing literature on the determinants of MFP growth into macroeconomic and institutional factors. We attempt to provide a reassessment and thematic survey of literature on the drivers of aggregate productivity, enabling policymakers to formulate effective economic policy.     

The next hundred years of growth and convergence

World gross domestic product per capita is forecast to grow at 2.6% annually over the next 100 years. Convergence of less-developed countries toward output levels of the world frontier accounts for much of the forecast. Projecting recent growth in China and India accounts for much of the forecast convergence. The forecast differs from the earlier literature because the facts of convergence have changed in recent decades. A Markov-switching model is estimated for each country, allowing each country to switch on or off a path of convergence to the world output frontier. Bayesian estimates of the historical process and posterior forecasts are offered.     

Pitfalls in estimating equilibrium exchange rates for transition economies

The literature on equilibrium exchange rates for the central and eastern European countries has mushroomed in recent years. In this paper, we discuss the econometric pitfalls involved in such estimations and endow the reader with the methodological ingredients to avoid such biases. We review the commonly used approaches and identify problems related to the most straightforward econometric procedures as they often do not take the transition process properly into account. As an alternative, we propose a two-stage “out-of-sample” strategy that consists of estimating the relationship between the exchange rates and fundamentals and the extrapolation of these relationships to transition economies.     

Theory of social transformation,political transition and economic growth

In this paper, I develop a model of sociopolitical transition that links the sociopolitical transformational process of countries to the dynamic process of output per capita and economic growth. Social polarization breeds discriminatory practices regarding government redistribution. This brings about inefficient allocation of resources away from production to political power struggle, leading to poor economic outcomes. However, the model shows that social integrative processes may correct this inefficiency over time depending on the degree of social fractionalization, the level of social distance between the groups, the level of production technology, etc. Even though the model predicts long-run convergence of growth rates and output per capita across countries, it shows possible prolonged divergence of these economic variables.     

Estimating Technological Change Using a Stochastic Frontier Production Function Framework: Evidence from U.S. Firm-Level Data

This paper presents a methodology for estimating an index of technological change using firm-level data in a stochastic frontier production function model that takes into account time-varying technical inefficiency. In contrast to the Solow divisia index approach, econometric estimation of the index with panel data allows the researcher to separate technical progress from the stochastic measurement error. Applying the econometric methodology to a panel of 908 publicly-traded U.S. firms from the COMPUSTAT database, we find evidence of a significant downturn in general technological change for the period, 1970– 1989, whereas the divisia index methodology applied to the same data shows stagnation. When the sample is divided into Manufacturing, Services, and Miscellaneous categories we find that estimates of technological change for the three groups display markedly different stochastic behavior and that the Services group is the source of the downturn.     

What have We Learnt from the Convergence Debate?

This paper surveys the convergence literature. It begins by laying out different definitions of convergence and by showing the link between the convergence issue and the growth theory debate. The paper then follows the convergence research conducted along four different approaches, namely the cross‐section, panel, time‐series, and distribution approaches. The paper shows the association of these methodological approaches with various definitions of convergence and highlights the connections among the convergence results. It shows that, despite some impressions to the contrary, there is considerable agreement among the results. Although the convergence research might not have solved the growth debate entirely, it has helped both the neoclassical and the new growth theories to adapt and evolve. The research on convergence has established new stylized facts regarding cross‐country growth regularities. It has brought to fore the existence of large technological and institutional differences across countries and has given rise to new methodologies for quantifying and analyzing these differences. This is providing a new information base for analysis of technological and institutional diffusion and for further development of growth theory in general.     

A stochastic dynamic model of trade and growth: Convergence and diversification

There is a growing literature that studies the properties of models that combine international trade and neoclassical growth theory, but mostly in a deterministic setting. In this paper we introduce uncertainty in a dynamic Heckscher-Ohlin model and characterize the equilibrium of a small open economy in such an environment. We show that, when trade is balanced period-by-period, the per capita output and consumption of a small open economy converge to an invariant distribution that is independent of the initial wealth. Further, at the invariant distribution, there are periods in which the small economy diversifies. Numerical simulations show that the speed of convergence increases with the size of the shocks. In the limit, when there is no uncertainty, there is no convergence and countries may specialize permanently. The paper highlights the role of market incompleteness, as a result of the period-by-period trade balance, in this setup. Through an analytical example we also illustrate the importance of country specific risk in delivering our results.     

Growth Empirics in Panel Data Under Model Uncertainty and Weak Exogeneity

This paper considers panel growth regressions in the presence of model uncertainty and reverse causality concerns. For this purpose, my econometric framework combines Bayesian model averaging with a suitable likelihood function for dynamic panel models with weakly exogenous regressors and fixed effects. An application of this econometric methodology to a panel of countries over the 1960–2000 period highlights the difficulties in identifying the sources of economic growth by means of cross‐country regressions. In particular, none of the nine candidate regressors considered can be labeled as a robust determinant of economic growth. Moreover, the estimated rate of conditional convergence is indistinguishable from zero. Copyright © 2014 John Wiley & Sons, Ltd.     

Embodying Embodiment in a Structural,Macroeconomic Input-Output Model

In this paper, I develop a regression-based system of labour productivity equations that account for capital-embodied technological change and I incorporate this system into IDLIFT, a structural, macroeconomic input-output model of the US economy. Builders of regression-based forecasting models have long had difficulty finding labour productivity equations that exhibit the "Solowian' property that movements in investment should cause accompanying movements in labour productivity. The production theory developed by Solow and others dictates that this causation is driven by the effect of traditional capital deepening as well as technological change embodied in capital. Lack of measurement of the latter has hampered the ability of researchers to estimate properly the productivity-investment relationship. Recent research by Wilson (2001) has alleviated this difficulty by estimating industry-level embodied technological change. In this paper, I utilize those estimates to construct capital stocks adjusted for technological change and then use these adjusted stocks to estimate Solow-type labour productivity equations. It is shown that replacing IDLIFT's former productivity equations, based on changes in output and time trends, with the new equations, results in a convergence between the dynamic behaviour of the model and that predicted by traditional (Solowian) production theory.     

Econometric modeling of technical change

The purpose of this paper is to present a new approach to econometric modeling of substitution and technical change. Substitution is determined by observable variables, such as prices of output and inputs and shares of inputs in the value of output. Our principal innovation is to represent the rate and biases of technical change by unobservable or latent variables. This representation is considerably more flexible than the constant time trends employed in the previous literature. An added advantage of the new representation is that the latent variables can be projected into the future, so that the rate and bias of technical change can be incorporated into econometric projections.     

人口老龄化条件下的经济平衡增长路径

本文将人口老龄化因素变量引入到索洛增长模型中，建立了包含人口老龄化因素变量的经济平衡增长路径方程，进而分析了人口老龄化因素对经济平衡增长路径的影响效应。由此在理论上证明了，人口老龄化因素对经济增长存在正、负或零等不同的作用效应，而相关的政策选择将影响人口老龄化的作用效应。     

Economic transition and growth

Some extensions of neoclassical growth models are discussed that allow for cross‐section heterogeneity among economies and evolution in rates of technological progress over time. The models offer a spectrum of transitional behavior among economies that includes convergence to a common steady‐state path as well as various forms of transitional divergence and convergence. Mechanisms for modeling such transitions, measuring them econometrically, assessing group behavior and selecting subgroups are developed in the paper. Some econometric issues with the commonly used augmented Solow regressions are pointed out, including problems of endogeneity and omitted variable bias which arise under conditions of transitional heterogeneity. Alternative regression methods for analyzing economic transition are given which lead to a new test of the convergence hypothesis and a new procedure for detecting club convergence clusters. Transition curves for individual economies and subgroups of economies are estimated in a series of empirical applications of the methods to regional US data, OECD data and Penn World Table data. Copyright © 2009 John Wiley & Sons, Ltd.     

Forecasting with nonstationary dynamic factor models

In this paper we analyze the structure and the forecasting performance of the dynamic factor model. It is shown that the forecasts obtained by the factor model imply shrinkage pooling terms, similar to the ones obtained from hierarchical Bayesian models that have been applied successfully in the econometric literature. Thus, the results obtained in this paper provide an additional justification for these and other types of pooling procedures. The expected decrease in MSE for using a factor model versus univariate ARIMA and shrinkage models are studied for the one factor model. Monte Carlo simulations are presented to illustrate this result. A factor model is also built to forecast GNP of European countries and it is shown that the factor model can provide a substantial improvement in forecasts with respect to both univariate and shrinkage univariate forecasts.     

Health human capital and economic growth in Sub-Saharan African and OECD countries

This paper investigates the effects of health human capital on the growth rate of per capita income in Sub-Saharan African and OECD countries. Using an expanded Solow growth model, panel data, and a dynamic panel estimator, we find that the growth rate of per capita income is strongly and positively influenced by the stock of, and investment in, health human capital after controlling for other variables. The stock of health human capital affects the growth rate of per capita income in a quadratic way: the growth impact of health human capital decreases at relatively large endowments of health stock. Our estimates suggest that 22% and 30% of the transition growth rate of per capita income in Sub-Saharan African and OECD countries respectively, can be attributed to health. The structure of the relationship between health human capital and the growth rate of income in Sub-Saharan African countries is similar to the structure of the relationship in OECD countries. This implies that increased stocks of health human capital leads to higher steady state income. Our results have interesting policy implications.     

Regional Convergence in Germany: a Geographically Weighted Regression Approach

Abstract

Regional convergence of German labour markets represents a politically important question. Different studies have examined convergence processes in Germany. We derive equations to estimate the speed of convergence on the basis of an extended Solow model. The technique of geographically weighted regression permits a detailed analysis of convergence processes, which has not been conducted for Germany as yet. It allows the estimation of a separate speed of convergence for every region resulting from the local coefficients of the regression equations. The application of this technique to German labour market regions shows regions moving at different speeds towards their steady states. The half-life periods in the model of conditional convergence disperse less than the same coefficients in the absolute convergence model. Moreover, the speed of convergence is substantially slower in the manufacturing sector than in the service sector.     

International output convergence: evidence from an autocorrelation function approach

This paper uses an autocorrelation function (ACF) approach to develop a new testing procedure for international output convergence. We define convergence in terms of sample ACFs of detrended output per capita, and construct an inference set‐up based on resampling and subsampling techniques for dependent data. Using per capita GDP for 15 OECD countries observed over a century, we find that the hypothesis of conditional convergence is unsupported; that, the USA apart, the linearized neoclassical growth model fails to replicate the transitional dynamics of OECD economies; and that these economies do not behave like a club. Copyright © 2008 John Wiley & Sons, Ltd.     

Exploring the economic rationale of extremes in GARCH generated betas The case of U.S. banks

The estimation of time varying beta is an important and growing area of research. The Multivariate GARCH model has been used in the literature to generate estimates of time varying betas. A common feature of the time varying risk estimates generated by this approach, is that they exhibit large outliers. In this paper, we investigate the incidence of such extreme beta observations in order to establish whether they are a response by the market to the arrival of news or alternatively are a result of the model picking up noise from the mean. Using daily data for a sample of U.S. deposit taking institutions over the period 1976 to 1994, this paper uses a Multivariate GARCH model to generate conditional beta estimates. The presence of large outliers is established and investigated. Generally, the results of this study suggest that these extreme observations are economically induced.