10 research outputs found

    Special issue on forecasting, use of survey data on expectations, and panel data applications: editors’ introduction

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    [First paragraph]This is a Special Issue of Empirical Economics (EE) in honor of Kajal Lahiri. Kajal is Distinguished Professor of Economics at SUNY- Albany. Kajal finished his Ph.D. in economics in 1975 from the University of Rochester. He has published over 120 articles in professional journals like the American Economic Review, Econometrica, Journal of Econometrics, JASA, JAMA, and written/coedited a number of books and journal volumes

    Health care expenditure and income in the OECD reconsidered: Evidence from panel data

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    This paper reconsiders the long-run economic relationship between health care expenditure and income using a panel of 20 OECD countries observed over the period 1971-2004. In particular, the paper studies the non-stationarity and cointegration properties between health care spending and income. This is done in a panel data context controlling for both cross- section dependence and unobserved heterogeneity. Cross-section dependence is modelled through a common factor model and through spatial dependence. Heterogeneity is handled through fixed effects in a panel homogeneous model and through a panel heterogeneous model. Our findings suggest that health care is a necessity rather than a luxury, with an elasticity much smaller than that estimated in previous studies

    Determinants of firm-level domestic sales and exports with spillovers: Evidence from China

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    This paper studies the determinants of firm-level revenues, as a measure of the performance of firms in China's domestic and export markets. The analysis of the determinants of the aforementioned outcomes calls for a mixed linear-nonlinear econometric approach. The paper proposes specifying a system of equations which is inspired by Basmann's work and recent theoretical work in international economics and conducts comparative static analyses regarding the role of exogenous shocks to the system to flesh out the relative importance of transmissions across outcomes

    Network effects on labor contracts of internal migrants in China: a spatial autoregressive model

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    This paper studies the fact that 37% of the internal migrants in China do not sign a labor contract with their employers, as revealed in a nationwide survey. These contract-free jobs pay lower hourly wages, require longer weekly work hours, and provide less insurance or on-the-job training than regular jobs with contracts. We find that the co-villager networks play an important role in a migrant’s decision on whether to accept such insecure and irregular jobs. By employing a comprehensive nationwide survey in 2011 in the spatial autoregressive logit model, we show that the common behavior of not signing contracts in the co-villager network increases the probability that a migrant accepts a contract-free job. We provide three possible explanations on how networks influence migrants’ contract decisions: job referral mechanism, limited information on contract benefits, and the “mini-labor union” formed among co-villagers, which substitutes for a formal contract. In the subsample analysis, we also find that the effects are larger for migrants whose jobs were introduced by their co-villagers, male migrants, migrants with rural Hukou, short-term migrants, and less educated migrants. The heterogeneous effects for migrants of different employer types, industries, and home provinces provide policy implications

    Structural changes in heterogeneous panels with endogenous regressors

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    This paper extends Pesaran's (Econometrica, 2006, 74, 967–1012) common correlated effects (CCE) by allowing for endogenous regressors in large heterogeneous panels with unknown common structural changes in slopes and error factor structure. Since endogenous regressors and structural breaks are often encountered in empirical studies with large panels, this extension makes Pesaran's CCE approach empirically more appealing. In addition to allowing for slope heterogeneity and cross‐sectional dependence, we find that Pesaran's CCE approach is also valid when dealing with unobservable factors in the presence of endogenous regressors and structural changes in slopes and error factor loadings. This is supported by Monte Carlo experiments

    Financial development, openess and institutions: Evidence from panel data

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    Utilising four annual panel datasets and dynamic panel data estimation procedures we find that trade and financial openness, as well as economic institutions are statistically important determinants of the variation in financial development across countries and over time since the 1980s. However, we find mixed support for the hypothesis that the simultaneous opening of both trade and capital accounts is necessary to promote financial development in a contemporary setting

    Robust linear static panel data models using Δ-contamination

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    The paper develops a general Bayesian framework for robust linear static panel data models using Δ -contamination. A two-step approach is employed to derive the conditional type-II maximum likelihood (ML-II) posterior distribution of the coefficients and individual effects. The ML-II posterior means are weighted averages of the Bayes estimator under a base prior and the data-dependent empirical Bayes estimator. Two-stage and three stage hierarchy estimators are developed and their finite sample performance is investigated through a series of Monte Carlo experiments. These include standard random effects as well as Mundlak-type, Chamberlain-type and Hausman-Taylor-type models. The simulation results underscore the relatively good performance of the three-stage hierarchy estimator. Within a single theoretical framework, our Bayesian approach encompasses a variety of specifications while conventional methods require separate estimators for each case

    Ethnic fractionalisation, governance and loan defaults in Africa

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    We present a theoretical model of an imperfectly competitive loans market that is suitable for emerging economies in Africa. The model allows for variation in both the level of contract enforcement (the quality of governance) and the degree of market segmentation (the level of ethnic fractionalization). The model predicts a specific form of non-linearity in the effects of these variables on loan default. Empirical analysis using African panel data for 110 individual banks in 28 countries over 2000-2008 provides strong evidence for these predictions. Our results have important implications for the conditions under which policy reform will enhance financial development

    Why Do African Banks Lend so Little?

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    We put forward a plausible explanation of African financial under-development in the form of a bad credit market equilibrium. Utilis- ing an appropriately modified IO model of banking, we show that the root of the problem could be unchecked moral hazard (strategic loan defaults) or adverse selection (a lack of good projects). Applying a dynamic panel estimator to a large sample of African banks, we show that loan defaults are a major factor inhibiting bank lending when the quality of regulation is poor. We also find that once a threshold level of regulatory quality has been reached, improvements in the default rate or regulatory quality do not matter, providing support for our theoretical predictions

    The African Credit Trap

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    We put forward a plausible explanation of African financial underdevelopment in the form of a bad credit market equilibrium. Utilising an appropriately modified IO model of banking, we show that the root of the problem could be unchecked moral hazard (strategic loan defaults) or adverse selection (a lack of good projects). We provide empirical evidence from a large panel of African banks which suggests that loan defaults are a major factor inhibiting bank lending when the quality of regulation is poor. We also find that once a threshold level of regulatory quality has been reached, improvements in the default rate or regulatory quality do not matter, providing support for our theoretical predictions
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