Cross-country Growth Regressions Research Articles

Short T dynamic panel data models with individual, time and interactive effects

SummaryThis paper proposes a transformed quasi‐maximum likelihood (TQML) estimator for short dynamic fixed effects panel data models allowing for interactive effects through a multifactor error structure. The proposed estimator is robust to the heterogeneity of the initial values and common unobserved effects, while at the same time allowing for standard fixed and time effects. It is applicable to both stationary and unit root cases. The order condition for identification of the number of interactive effects is established, and conditions are derived under which the parameters are locally identified. It is shown that global identification in the presence of the lagged dependent variable cannot be guaranteed. The TQML estimator is proven to be consistent and asymptotically normally distributed. A sequential multiple testing likelihood ratio procedure is also proposed for estimation of the number of factors which is shown to be consistent. Finite sample results obtained from Monte Carlo simulations show that the proposed procedure for determining the number of factors performs very well, and the TQML estimator has small bias and root mean square error (RMSE) and correct empirical size in most settings. The practical use of the TQML approach is demonstrated by means of two empirical illustrations from the literature on cross county crime rates and cross country growth regressions.

Growth accounting, development accounting and cross-country growth regressions: A conceptual review essay

Background: This review article sets out to identify certain critiques of growth accounting, development accounting and cross-country growth regressions. These critiques provide insights relevant to the usefulness and policy relevance of these methods.Aim: The aim of this article was to critically review literature and to provide a synthesis of this literature, deriving certain arguments to contribute to further research.Method: This article takes the form of a critical review essay.Results: Growth accounting, development accounting and cross-country growth regressions all have some limitations and knowledge of their strengths and weaknesses may be helpful for those who are undertaking transdisciplinary social science research using these methods. These methods seem to suffer from similar criticisms levelled at neoclassical thinking, which need to be considered more seriously in the literature.Conclusion: Further research should explore how such methods might complement each other to improve validity of research findings.

The empirics of economic growth over time and across nations: a unified growth perspective

This research develops an expanded unified growth theory that incorporates the endogenous accumulation of physical capital, population, human capital, and technology. The model incorporates a complementarity between physical capital and human capital and can be extended to a multi-country setting with international technology diffusion. The analytical characterization of the mechanisms behind the observed patterns of long-run growth and comparative development delivers a consistent explanation for a large set of seemingly unrelated empirical facts. A quantitative multi-country version of the model matches various empirical regularities of long-run growth dynamics and comparative development patterns that have previously been studied in isolation. The findings also shed new light on the role of the demographic transition for convergence patterns, the specification of cross-country growth regressions, technology spillovers, and the secular stagnation debate.

Imported Intermediate Goods and Economic Growth

Purpose - This research aims to provide empirical evidence that highlights the importance of imported intermediate goods in long-term economic growth. To this end, this paper develops an index that measures the productivity gains associated with a country’s intermediate goods imports using highly disaggregated trade data. Design/methodology - The basic hypothesis is that countries sourcing higher-productivity (or higher-quality) inputs from developed economies derive a larger benefit from foreign R&D. To explore this hypothesis, standard cross-country growth regressions are performed using the highly disaggregated data from the United Nations (UN) Commodity Trade Statistics Database (COMTRADE). To address the endogeneity issue, I apply an instrumental variable (IV) approach. Findings - The results of this study demonstrate that the index predicts subsequent economic growth in middle- and low-income countries. This finding is consistent with previous studies that have argued that developing countries can achieve substantial productivity gains by importing intermediate inputs from developed countries. By contrast, there is no evidence of a significant association between the index and economic growth in high-income countries. Originality/value - This paper contributes to our understanding of the causal relationship between international trade and economic growth. From an economic policy perspective, the results suggest that developing countries with limited technology endowment can boost growth from input-tariff liberalization.

Revisiting the Solow growth model: new empirical evidence on the convergence debate

PurposeThis paper investigates income convergence using different convergence concepts and methodologies for 72 countries over the period between 1960 and 2010.Design/methodology/approachThis study applies beta (β), sigma (s), stochastic and club convergence approaches. For β-convergence analysis, it derives the cross-country growth regressions of the Solow growth model under the basic and augmented Cobb–Douglass (CD) production functions and estimates them using cross-section and panel data estimators. While it employs both the widely used coefficient of variation and recently developed weak s-convergence approaches for s-convergence, it applies three different unit root tests for stochastic convergence. To test club convergence, it estimates the log-t regression.FindingsThe results reveal that (1) there exists conditional β-convergence, meaning that poorer countries grow faster than richer countries; (2) income per worker is not (weakly) s-converging, and cross-sectional variation does not tend to fall over the years; (3) stochastic convergence is not found and (4) countries in the sample do not converge to the unique equilibrium, and there exist five distinctive convergence clubs.Research limitations/implicationsThe results clearly show that heavily relying on one of the convergence techniques might lead researchers to obtain misleading results regarding the existence of convergence. Therefore, to draw reliable inferences, the results should be checked using different convergence concepts and methodologies.Originality/valueContrary to the previous literature, which is generally restricted to testing the existence of absolute and conditional β-convergence between countries, to the best of the author’s knowledge, this is the first study to consider and compare all originally and recently developed fundamental concepts of convergence altogether. Besides, it uses the Penn World Table (PWT) 9.1 and extends the period to 2010. From this point of view, this study is believed to provide the most up-to-date empirical evidence.

Taxation and growth: Why does it matter and how can it be analysed?

AbstractThe growth impact of tax reforms is probably one of the most controversial issues in economic policy discussions, reflecting deep beliefs in the way economic agents are expected to react to policy changes. The optimal tax theory literature provides a wide array of arguments to identify the mechanisms through which tax reforms might influence growth, depending on the tax category considered and the circumstances under which tax reforms are implemented. The empirical literature has relied on the use of cross-country growth regressions and provided general results leading to normative conclusions on the desirability of specific tax reform options. However, recent research has shown that this approach yields inconclusive results, notably due to identification and endogeneity issues, and the difficulty to account for the true determinants of governments' actions. The dynamic scoring approach combining microsimulation and macro models proves more useful in this respect, especially in order to draw policy recommendations while accounting for the second-round effects of tax reforms. I illustrate these arguments by analysing the growth impact of a hypothetical change from the current flat personal income tax (PIT) rates to progressive taxes in Central and Eastern European (CEE) countries. I find that the estimated impact of such a reform would be rather small but positive when using the dynamic scoring method, while the less-reliable traditional growth regressions would suggest adverse growth effects.

Short T Dynamic Panel Data Models with Individual and Interactive Time Effects

This paper proposes a transformed quasi maximum likelihood (TQML) estimator for short T dynamic fixed effects panel data models allowing for interactive effects through a multi-factor error structure. The proposed estimator is robust to the heterogeneity of the initial values and common unobserved effects, whilst at the same time allowing for standard fixed and time effects. It is applicable to both stationary and unit root cases. The order condition for identification of the number of interactive effects is established, and conditions are derived under which the parameters are almost surely locally identified. It is shown that global identification in the presence of the lagged dependent variable cannot be guaranteed. The TQML estimator is proven to be consistent and asymptotically normally distributed. A sequential multiple testing likelihood ratio procedure is also proposed for estimation of the number of factors which is shown to be consistent. Finite sample results obtained from Monte Carlo simulations show that the proposed procedure for determining the number of factors performs very well and the TQML estimator has small bias and RMSE, and correct empirical size in most settings. The practical use of the TQML approach is demonstrated by means of two empirical illustrations from the literature on cross county crime rates and cross country growth regressions.

Determinants of economic growth: Different time different answer?

Almost all studies that use Bayesian model averaging to identify robust growth determinants focus on the growth period between 1960 and the 1990s. We apply Bayesian Model Averaging to a rolling time window of 20 and 35 years using a newly compiled dataset with 37 growth determinants for the years 1960 to 2010. Our findings indicate instabilities in the inferences on growth determinants across growth periods. In line with prior research, we find support for robust ambiguity in early growth periods, that is, cross-country growth regressions provide little support for some growth determinants being more important than others. However, determinants related to demography, education, trade, investment and to some extent religion seem to matter in the subsequent growth periods with education and demography being most important in recent growth periods.

The deep determinants of economic development in China—a provincial perspective

There is a significant body of literature arguing that institutional quality is the key for long run economic growth and development. While the majority of these studies are based on cross-country growth regressions, we focus on the institution-economic growth nexus within a particular country, namely China. China is often regarded as an exception by having achieved miraculous growth for more than three decades despite relatively low institutional quality. Nonetheless, our findings suggest that at the provincial level, institutional quality played in fact an important role for the economic success of a province in China, even more important than geography and integration. However, when simultaneously examining the relationship between institutions, human capital, and economic development, we find that human capital ‘trumps’ everything else; however institutional quality has a highly significant indirect effect on provincial per capita income by improving human capital. We employ, among others, instrumental variable estimation techniques to address endogeneity problems.

'Finance And Growth' Re-Loaded

We assess the relationship between finance and growth over the period 1980-2014. We estimate a cross-country growth regression for 48 countries during 20 periods of 15 years starting in 1980 (to 1995) and ending in 1999 (to 2014). We use OLS and IV estimations and we find that: 1) overall financial development had a positive effect on economic growth during all periods of our sample, i.e., we confirm that from 1980 to 2014 financial services provided by the various financial systems were significant (to various degrees) for firm creation, industrial expansion and economic growth; but that, 2) the structure of financial markets was particularly relevant for economic growth until the financial crisis; while 3) the structure of the banking sector played a major role since; and finally that, 4) the legal system is the primary determinant of the effectiveness of the overall financial system in facilitating innovation and growth in (almost) all of our sample period. Hence, overall our results suggest that the relationship between finance and growth matters but also that it varies over time in strength and in sector origination.

The Deep Determinants of Economic Development in China A Provincial Perspective

There is a significant body of literature arguing that institutional quality is the key for long run economic growth and development. While the majority of these studies are based on cross-country growth regression, in our paper, we focus on the institution-economic growth nexus within a particular country, namely China. China is often regarded as an exception by having achieved miraculous growth for more than three decades despite relatively low institutional quality. However, our key findings suggest that at the provincial level, institutional quality played in fact an important role for the economic success of a province in China, “trumping” geographical factors and integration which only have an indirect effect by influencing institutional quality. We employ instrumental variable estimation techniques to address the endogeneity problems regarding the institutions-development relationship.

Of needles and haystacks: revisiting growth determinants by robust Bayesian variable selection

This paper proposes a Bayesian variable selection technique that is robust to model uncertainty and heteroscedasticity of unknown forms in cross-country growth regressions. In particular, we adopt a spike-and-slab prior for the regression coefficients to sidestep the potential complications of highly collinear covariates in the variable selection problems. We find a number of important growth determinants that are distinct from the previous works in the ranking and sign of estimated coefficients, partly because of the presence of highly correlated covariates. Importantly, we find that our results from variable selection are not qualitatively changed when various degrees of freedom for t-errors are considered. The implications of this work highlight the caution needed in empirical growth research when using g-priors under collinearity.

Institutions and economic growth in transition countries — new experiences and implications from financial crisis 2007–2010 (Part 1)

Motivation: Cross-country growth regressions indicate that institutions are important for growth. Some institutions are created, protected and enforced by the government — they are the institutions of state. The most important for economic growth are: economic freedom and protection of property rights, political freedom (or democracy), quality of governance and the rule of law. The changes that took place after 1989 in the countries of Central-Eastern Europe were not only political but also economic. The post-socialist transition was, above all, a change of the institutions of state. It was a kind of the so-called ‘quasi-natural experiment’. Therefore, my intention is to answer the question: how the institutions of state affect economic growth in transition countries. Aim: The aim is to identify the impact state institutions had on the economic growth in transition countries during the financial crisis of 2007–2010. Results: In the first part of this article I review the literature and present hypothesis about dependency of economic growth and institutions during the financial crisis in transition countries. In the relevant literature there is a consensus that without an appropriate institutional background, market incentives do not lead to optimal resource allocation. Institutions have a particularly crucial impact in the case of post-socialist countries which have undergone political and economic transition. A significant and positive impact on economic growth rate is exercised by such institutions as: protection of property rights and political stabilization, government efficiency and rule of law. The experiences of transition countries confirm also the significance of economic freedom for economic situation.

Institutions and economic growth in transition countries — new experiences and implications from financial crisis 2007–2010 (Part 2)

Motivation: Cross-country growth regressions indicate that institutions are important for growth. Some institutions are created, protected and enforced by the government — they are the institutions of state. The most important for economic growth are: economic freedom and protection of property rights, political freedom (or democracy), quality of governance and the rule of law. Institutions are especially important in transition countries. Two questions arise: were institutions important for economic growth in transition countries during the financial crisis? What happened to the institutions of state during the financial crisis? Aim: The aim of the second part of this article is to verify two hypothesis about institutions and economic growth in transition countries, which were put forward in the first part of this article. In order to estimate the relationship between institutions and economic growth in transition countries during the crisis, a cross-sectional regression was conducted. Additionally the Granger causality test was conducted. Results: The obtained results indicate that during the recession, in countries were before the crisis the institutions were worse, the pace of the economic growth was greater (hypothesis 1 should be rejected). In order to verify hypothesis 2 that the economic growth contributes to changes in state institutions in such a way that the faster the pace of growth the greater the improvement in state institutions a cross-sectional regression was used and the Granger causality test was conducted. Obtained results do not confirm the hypothesis 2. The estimates of parameters were in line with the expectations but statistically insignificant.

What Type of Finance Matters for Growth? Bayesian Model Averaging Evidence

This paper examines the effect of finance on long-term economic growth using Bayesian model averaging to address model uncertainty in cross-country growth regressions. The literature largely focuses on financial indicators that assess the financial depth of banks and stock markets. These indicators are examined jointly with newly developed indicators that assess the stability and efficiency of financial markets. Once the finance-growth regressions are subjected to model uncertainty,the results suggest that commonly used indicators of financial development are not robustly related to long-term growth. However, the findings from the global sample indicate that one newly developed indicator -- the efficiency of financial intermediaries -- is robustly related to long-term growth.

On the Effect of Prior Assumptions in Bayesian Model Averaging With Applications to Growth Regression

We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors and on predictive performance. We illustrate these issues in the context of cross-country growth regressions using three datasets with 41 to 67 potential drivers of growth and 72 to 93 observations. Finally, we recommend priors for use in this and related contexts.

Trade openness, income, and role of institutions: A revisit using heterogeneous panel data models

AbstractThe positive association between trade openness and income has been debated over years due to serious estimation flaws prevailing in the cross-country empirical trade literature. The present paper contributes to this debate by re-examining the long-run relationship between trade openness and income per capita focusing on role of institutions. It does so by estimating a heterogeneous panel data model with 97 countries over the period 1980–2012 taking unobserved common factors into consideration. Our method is a more appropriate approach to estimate this relationship given the potential cross-section dependence and parameter heterogeneity associated with cross-country growth regressions. The results have found evidence to suggest that trade openness is positively and significantly associated with income per capita even after controlling for parameter heterogeneity, cross-section dependence and possible endogeneity. Results further suggest that better quality institutions complement the effects on in...

The resource curse: A statistical mirage?

A surprising feature of resource-rich economies is slow growth. It is often argued that natural-resource production impedes development by creating market or institutional failures. This paper establishes an alternative explanation—a slow-growing resource sector. A declining resource sector is disproportionately reflected in resource-dependent countries. Additionally, there is little evidence that resource dependence impedes growth in non-resource sectors. More generally, this paper illustrates the importance of considering industry composition in cross-country growth regressions.

Distribution theory of the least squares averaging estimator

This paper derives the limiting distributions of least squares averaging estimators for linear regression models in a local asymptotic framework. We show that the averaging estimators with fixed weights are asymptotically normal and then develop a plug-in averaging estimator that minimizes the sample analog of the asymptotic mean squared error. We investigate the focused information criterion (Claeskens and Hjort, 2003), the plug-in averaging estimator, the Mallows model averaging estimator (Hansen, 2007), and the jackknife model averaging estimator (Hansen and Racine, 2012). We find that the asymptotic distributions of averaging estimators with data-dependent weights are nonstandard and cannot be approximated by simulation. To address this issue, we propose a simple procedure to construct valid confidence intervals with improved coverage probability. Monte Carlo simulations show that the plug-in averaging estimator generally has smaller expected squared error than other existing model averaging methods, and the coverage probability of proposed confidence intervals achieves the nominal level. As an empirical illustration, the proposed methodology is applied to cross-country growth regressions.

How Ethnic Diversity Affects Economic Growth

Summary This paper investigates the empirical relationship between ethnic diversity, polarization, and economic growth. Ethnicity is assumed to affect economic growth through a number of possible transmission channels that are generally included in cross-country growth regressions. This paper provides an extensive empirical analysis shedding light on the various sources through which ethnic diversity and polarization affects economic growth indirectly. It advances and empirically establishes the hypothesis that ethnic diversity has a strong direct negative impact on economic growth, whereas ethnic polarization has non-negligible indirect economic effects through the specified channel variables.