Organized crime and public spending: a panel data analysis

The aim of this paper is to investigate, empirically, what components of public spending imply a decreasing effect on organized crime and what components create opportunities for organized crime, discussing also the role of government efficiency. Using a panel data analysis, the results show a strikingly consistent pattern for the EU Member States. Organized crime mainly operates in the distribution of government spending for local public goods and public provision of private services. There is a decreasing effect on organized crime of the public expenditure devoted to education and social policy. Government efficiency in public spending is beneficial to limit the opportunities of the organized crime.     

Testing for time-invariant unobserved heterogeneity in generalized linear models for panel data

Recent literature on panel data emphasizes the importance of accounting for time-varying unobservable individual effects, which may stem from either omitted individual characteristics or macro-level shocks that affect each individual unit differently. In this paper, we propose a simple specification test of the null hypothesis that the individual effects are time-invariant against the alternative that they are time-varying. Our test is an application of Hausman (1978) testing procedure and can be used for any generalized linear model for panel data that admits a sufficient statistic for the individual effect. This is a wide class of models which includes the Gaussian linear model and a variety of nonlinear models typically employed for discrete or categorical outcomes. The basic idea of the test is to compare two alternative estimators of the model parameters based on two different formulations of the conditional maximum likelihood method. Our approach does not require assumptions on the distribution of unobserved heterogeneity, nor it requires the latter to be independent of the regressors in the model. We investigate the finite sample properties of the test through a set of Monte Carlo experiments. Our results show that the test performs well, with small size distortions and good power properties. We use a health economics example based on data from the Health and Retirement Study to illustrate the proposed test.     

Developed stock market reaction to political change: a panel data analysis

This paper utilized panel data to examine the effects of political change in developed stock market. According to Hausman test, we capture the stock return by the fixed-effect model to fit the stock market. Political change was originally intended as an incumbent party impetus to create opportunities for progress. However, this has caused great political party distress, creating political change with an inverse stock return relationship in developed countries.     

Semiparametric Bayesian inference for dynamic Tobit panel data models with unobserved heterogeneity

This paper develops semiparametric Bayesian methods for inference of dynamic Tobit panel data models. Our approach requires that the conditional mean dependence of the unobserved heterogeneity on the initial conditions and the strictly exogenous variables be specified. Important quantities of economic interest such as the average partial effect and average transition probabilities can be readily obtained as a by‐product of the Markov chain Monte Carlo run. We apply our method to study female labor supply using a panel data set from the National Longitudinal Survey of Youth 1979. Copyright © 2008 John Wiley & Sons, Ltd.     

Capital market integration in ASEAN: A non-stationary panel data analysis

Motivated by the establishment of ASEAN Economic Community (AEC) at the end of 2015, we examine saving-investment relationship in various subgroups of ASEAN to assess their capital market integration. The results from second generation panel unit-root and cointegration tests that account for cross-sectional dependence as well as estimates of long-run saving-retention rate provide some evidence of market integration in ASEAN. The analysis of short-run dynamics suggests that capital mobility in ASEAN during 1980–2014 appears similar to that in OECD countries during 1970–1999. More importantly, across different panel estimators and subgroups of membership, there is considerable heterogeneity among the member countries. The saving-investment association is very weak, thereby implying very high capital mobility, in more developed members such as Singapore, Malaysia, and Brunei; the association is very strong, implying very low capital mobility, for much less developed members such as Laos, Myanmar, and Cambodia. The results call for renewed effort to develop capital markets in less developed nations and integrate them with the rest of the membership in ASEAN. In this paper, we also address several major shortcomings of the original Feldstein-Horioka framework.     

Further evidence on finance-growth causality: A panel data analysis

This paper reassesses the causal relationship between financial development and economic growth. Using recently developed panel methods on a data set of 71 developed and developing countries over the period 1960-2004, our study confirms previous results of a bidirectional causality between finance and growth. In addition, we show significant differences among country groups when considering both long-run and short-run causality. While in low and middle income countries there is no supportive evidence of short-run causality between financial development and economic growth, in high income countries economic growth significantly affects financial development.     

Financial development and governance: A panel data analysis incorporating cross-sectional dependence

This study investigates bidirectional causality between governance and financial development using panel data of 101 countries from 1984 to 2013. The financial development–governance nexus is explored using econometric methods robust to cross-sectional dependence, and the relationship between different levels of development and openness is analyzed. Long-run equation estimates show clear evidence that financial development positively affects governance, and this positive impact is found to be robust to three different measures of governance. Further analysis shows that improving governance quality has a positive effect on financial development, while Granger causality tests demonstrate bidirectional causality between financial development and the governance measures. Finally, the impact of financial development on governance is dependent on a country’s level of development and openness. These findings underscore the crucial role of financial development in bringing about good governance reforms and economic growth that, in turn, can further develop the financial sector. As such, a symbiotic and synergistic relationship can persist between good governance, growth, and financial development. The findings provide significant motivation for policymakers to encourage openness and financial sector development to lift the standard of living, especially in emerging economies.     

A panel data analysis for housing affordability in Taiwan

Although the equilibrium relationship between household income and house price is well documented in previous theoretical studies, the empirical results are usually unfavorable. This article examines whether a long-term relationship between house price and income exists through a panel integration and cointegration methodology in analyzing data from four cities in Taiwan from 1980 to 2007. The findings support the existence of a long-term equilibrium relationship between income and house price, which indicate that housing affordability in Taiwan is stable. After controlling other variables, the income elasticity of house prices on average is close to one. Furthermore, evidence points to a bi-directional causality between income and house price.     

The major determinants of logistic performance in a global perspective: evidence from panel data analysis

The global logistics industry has grown significantly and logistics has become an important sector of the business economic system and a major global economic activity in recent years. Logistics activities accelerate economic and productivity growth. Efficient logistics is also important to a country’s competitiveness and source of employment. The purpose of this paper is to uncover and understand the major determinants of logistics performance (LP) to further lift the LP of countries. Using unbalanced panel data of 93 selected countries from 2007 to 2014, the present research attempts to critically investigate the major determinants of LP. In estimating the model, this study prefers to use static panel data approach owing to limited data. The findings of the present study reveal that (a) countries with low level of corruption and stable political environment are likely to yield a high level of LP; (b) improvement in resources supply such as infrastructure, technology, labour, and education also have a significant positive effect on LP. Therefore, institutional reforms and upgrading resources will effectively accelerate LP.     

Exploring the role of FDI in enhancing the entrepreneurial activity in Europe: a panel data analysis

This paper explores the impact of foreign direct investment (FDI) on the entrepreneurial activity in 16 European countries. By using Global Entrepreneurship Monitor (GEM) data, which enables the distinction necessity-driven vs. opportunity-driven entrepreneurs, we assess the influence of both inward and outward FDI on the entrepreneurial activity during the time span 2005–2012. We resort to a static, as well as to a dynamic panel data analysis. Our findings highlight the fact that the FDI has no clear influence on the total entrepreneurial activity, or on the established business ownership rate. Nevertheless, our results clearly state that both inward and outward FDI positively influences the necessity-driven entrepreneurs, while having a negative impact on the opportunity-driven entrepreneurs. The results prove to be robust regarding the use of a fixed and random effects panel model, two stages least square (2SLS) model, as well as the use of a system-Generalized Method of Moments (system-GMM) approach.     

Measurement error in causal analysis of panel data: Attenuated versus inflated relationships

The presence of random measurement error is commonly thought to cause attenuation of statistical relationships. While this is an unquestionable truth in bivariate analysis, it cannot be generalized to the multivariate case without qualification. This paper shows that measurement error may give rise to overestimates of parameters in causal analysis whenever there is more than one independent variable and the independent variables are correlated. If the independent variables are not measured with the same amount of reliability, there may also be considerable error in estimates of the relative magnitude of their impact. Both problems are particularly serious when the amount of measurement error is large relative to some of the causal effects such as in panel analysis with lagged dependent variables.     

Institutions and economic development: A Granger causality analysis of panel data evidence

This study examines the causal relationship between institutions and economic development using a panel Granger causality test. The study incorporates two institutional datasets, the International Country Risk Guide (ICRG) and World Governance Indicators (WGI). The empirical results based on 60 countries show that there is a bi-directional causality between institutions and economic development. The findings also suggest that causality patterns between institutions and economic performance vary at different stages of income level. Better institutional quality fosters economic development in higher income countries, whereas economic development tends to enhance institutional quality in lower income countries.     

Environmental taxes,reforms and economic growth: an empirical analysis of panel data

This paper explores the relationship between environmentally related taxes and the economic growth rate. The analysis also investigates whether this relationship differs between countries that have implemented environmental tax reforms (ETRs) and those that have not. Using panel data from 31 OECD countries over the period 1994–2013, the paper finds that when we allow environmentally related tax revenues to interact with an initial level of real GDP per capita, the overall revenues of these taxes are negatively associated with the economic growth rate in the short and long term. Furthermore, we show that the higher the initial level of GDP per capita, the more environmentally related tax revenues can promote the economic growth rate. The analysis also reveals that the relationship between environmentally related tax revenues and economic growth varies between countries that have a mechanism to redistribute environmentally related tax revenues and those that do not.     

Wealth dynamics: reducing noise in panel data

Although the asset data from the Health and Retirement Study (HRS) is of very high quality, there is sufficient noise to frustrate attempts to study saving behaviour by examining wave‐to‐wave change in wealth. In this research, we attempt to reduce noise by means of reactive‐dependent interviewing in which respondents with large inexplicable changes in assets between 1998 and 2000 are called back by HRS interviewers, presented with their prior reports and asked to reconcile the data. We achieved reconciliation for 1255 households (2479 net‐worth components) and, as a result, the variance in measured change for the entire sample of 11,583 households with the same financial respondents in both waves was cut in half. The empirical validity of the data also appears to have been improved. The correlation of gross change in net worth and income, for instance, increased from an insignificant negative to a highly significant positive value. Although reconciliation of large asset changes marginally improves the goodness of fit of multivariate models, there remains sufficient noise in the asset‐change data to require analysts to employ additional methods to reduce the influence of outliers. Copyright © 2006 John Wiley & Sons, Ltd.     

Simple solutions to the initial conditions problem in dynamic,nonlinear panel data models with unobserved heterogeneity

I study a simple, widely applicable approach to handling the initial conditions problem in dynamic, nonlinear unobserved effects models. Rather than attempting to obtain the joint distribution of all outcomes of the endogenous variables, I propose finding the distribution conditional on the initial value (and the observed history of strictly exogenous explanatory variables). The approach is flexible, and results in simple estimation strategies for at least three leading dynamic, nonlinear models: probit, Tobit and Poisson regression. I treat the general problem of estimating average partial effects, and show that simple estimators exist for important special cases. Copyright © 2005 John Wiley & Sons, Ltd.     

Homogeneity pursuit in panel data models: Theory and application

This paper studies the estimation of a panel data model with latent structures where individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we design an algorithm called Panel‐CARDS. We show that it can identify the true group structure asymptotically and estimate the model parameters consistently at the same time. Simulations evaluate the performance and corroborate the asymptotic theory in several practical design settings. The empirical application reveals the heterogeneous grouping effect of income on democracy.     

The impact of institutional quality on manufacturing sectors: A panel data analysis

We use data on Russian regions to examine the effect of institutional quality on institutionally dependent manufacturing sectors in terms of both output levels and growth rates. Unlike the existing literature on this topic, which mostly uses cross-sectional or pooled specifications for either country-level or regional data, we use panel data. This approach allows us to distinguish between short-term and long-term impacts and mitigates endogeneity concerns. As an additional contribution to the literature, we estimate the full marginal effects of institutions on manufacturing sectors with different degrees of institutional dependence. In terms of policy recommendations, our results imply that significant institutional improvements would be needed for the Russian economy to diversify away from heavy reliance on oil and natural gas.     

Economic development and growth in Colombia: An empirical analysis with super-efficiency DEA and panel data models

In this paper, we analyse economic development and growth through traditional measures (gross domestic product and human development index) and Data Envelopment Analysis (DEA) in Colombian departments over the period 1993–2007. We use a DEA model to measure and rank economic development and growth from different approaches such as poverty, equality and security. The results show considerable variation in efficiency scores across departments. A second-stage panel data analysis with fixed effects reveals that higher levels of economic activity, quality life, employment and security are associated with a higher efficiency score based on the standards of living, poverty, equality and security. All findings of this analysis should demonstrate that economic development and growth could be achieved most effectively through a decrease in poverty, an increase in equality, a reduction in violence, and improved security. This indicates the need to generate effective policies that guarantee the achievement of these elements in the interest of all members of society.