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This paper aims to use the approach based on the application of the law of gravity for the study of the flows of export and the effects of the RTAs.

In this paper, the authors evaluate the effects of RTAs on exports between members and non-members taking into account the Vinerian specification. The authors also try to estimate the impact of the recent economic crisis on the flows of export and the success of the RTAs. The authors use a model of static and dynamic gravity for 40 countries and six RTAs during the period 1980-2011.

Definitely the proliferation of RTAs will continue to be one of the driving forces that will constitute the political system and the global economy in the following years. It indicates a process that implies the merger of economies separated in bigger regions of free trade. Regional integration is seen as beneficial in many senses and is the major economic objectives in addition to presenting a stabilizing factor in international relations.

The gravity model is estimated using the last techniques of panel data which takes into account the endogeneity of the effects of integration and the existence of dynamic effect.

The purpose of this study is to investigate the impact on income distribution from foreign investment and open trade. The research highlights the impact of multinational enterprises (MNEs) on inequality in Western Balkan (WB) countries from 2007 to 2019. The study seeks to answer a critical question: how do multinational corporations affect income distribution?

The study uses different techniques such as two-stage least squared, fixed and random effect estimators and generalised method of moments (GMM). The data was gathered from the United Nations Development Programme, World Bank Indicators (WB) and Slot’s World Standardised Income Inequality Database.

The interaction of multinational companies through foreign direct investment (FDI) has a significant impact on income inequality. This research paper indicates that the effect of FDI on income inequality is significant and has a negative effect on income inequality within WB countries. The results from the GMM estimator, therefore, demonstrate the hypothesis that multinational companies have a positive effect in WBs countries on reducing inequality.

The theoretical contribution that this paper seeks to make is by the applying of incremental changing dimension or more specifically, through expanding existing knowledge. Based on a study of the prior articles, the authors found out that the majority of the papers discussed only income inequality or economic inequality or rarely education, but none of the papers examined all classifications of inequality in one paper. This paper’s second contribution is to calculate inequality not only by the Gini coefficient but also by the human development index. The study is unique in that it is the first to assess the impact of FDI on income distribution in WB countries. The research is unique in that it attempts to shed light on the impact of multinational corporations on inequality in Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia and Serbia. The findings of this study will help to develop new policies, new legislation, reducing inequity and support FDIs and MNEs for governments and policymakers.

The purpose of this paper is to investigate the determinants of portfolio equity flows to the Sub-Saharan African (SSA) region over the period 1996-2010.

The study uses a sample of 14 SSA countries to estimate the baseline regression through employing the system generalized methods of moment dynamic panel estimation framework. To check the robustness of the estimation results, the study further analyses the data set using the random effects-generalized least squares (EGLS) estimator. The Random effects-generalized least squares estimator is also referred to a the Estimated Generalized least Squares (EGLS) estimator.

The paper finds a significant positive relationship between financial development and portfolio equity flows. Furthermore, while the study surprisingly finds trade openness to have a significant negative relationship, political stability is found to have a significant positive relationship with portfolio equity. To check for the robustness of these results, the authors further analyse the data set using the random EGLS estimator. The result of the EGLS estimator confirms that there is a robust positive relationship between financial development and portfolio equity flows to SSA. However, the results suggest that neither trade openness nor political stability is a robust determinant of portfolio equity flows to the sub-region.

Policy measures should aim at enhancing financial sector development, political stability and rule of law. A transparent judicial system that enhances rule of law and deepens democratic governance in countries in the sub-region is critical, but even more critical is deepening the financial sector, given the important role financial development plays in portfolio equity flows as suggested by the findings. A range of measures and appropriate policy responses are therefore needed for countries that have to manage macroeconomic and financial stability risks to deepen the financial sector.

Most studies on private capital flows to SSA have focussed on foreign direct investment flows with no or scanty evidence on the drivers of portfolio equity flows. This study fills this gap in the literature.

While the relationship between military expenditure and economic growth during the Cold War period is well-researched, relatively less is known on the issue for the post-Cold War era. Equally how the relationship varies with respect to exposure to conflict is also not fully examined. Therefore, the purpose of this paper is to investigate the causal impact of military expenditure on growth in the presence of internal and external threats for the period 1990-2013 using data from 70 developing countries.

The main estimates are based on the generalized method of moments (GMM) regression model. But for comparison purposes, the authors also report estimates using fixed and random effects as well as pooled cross-section regressions. The regression specification accounts for non-linear effect of military expenditure allowing for interaction with conflict variable (where distinction is made between external and internal conflict).

The analysis indicates that methods as well as model specification matter in studying the effect of military spending on growth. Full sample estimates based on GMM, fixed, and random effects models suggest a negative and statistically significant effect of military expenditure. However, fixed effects estimate becomes insignificant for low-income countries. The effect of military spending is also insignificant in the cross-sectional OLS model if conflict is not considered. When the regression model additionally controls for conflict, the effect of military spending conditional upon (internal) conflict exposure is significant and positive. No such effect is present conditional upon external threat.

One important limitation of the analysis is the small sample size – the authors had to restrict analysis to 70 low and middle-income countries for which the authors could construct post-Cold War panel data on military expenditure along with information on armed conflict exposure (the later from the Uppsala Conflict Data Program, 2015).

To the best of the author’s knowledge, this is the first paper to examine the joint impact of military expenditure and conflict on economic growth in post-Cold War period in a sample of developing countries. Moreover, an attempt is made to review and revisit the large Cold War literature where studies vary considerably in terms findings. A key reason for this is the somewhat ad hoc choice of econometric methods – most rely on cross-section data and rarely conduct sensitivity analysis. The authors instead rely on panel data estimates but also report results based on naïve models for comparison purposes.

The purpose of this paper is to focus on the role of unions for job flow rates.

The author uses a longitudinal data set emphasizing the importance of the time dimension.

Using the fixed effects estimator, the author finds that unions decrease the job separation rate and the job finding rate.

The findings support that the implications of the insider-outsider model by Lindbeck and Snower (1986): unions are beneficial for insiders but harm outsiders.

Hedonic models are commonly used in housing markets studies to obtain quantitative measures of various implicit prices. The use of panel data in other fields of research has proved to be valuable when accounting for unobserved heterogeneity. Given that houses are extremely heterogeneous, and given that it is impossible to include all relevant attributes in hedonic models, removing unobserved heterogeneity by basic panel data models sounds appealing. This paper seeks to compare results between models that use pooled cross section data and panel data. The main research question is whether the pooled model gives unbiased estimates on some basic implicit prices.

The paper applies the hedonic methodology. It uses regression analysis and estimate basic and parsimonious models that use either pooled time series and cross section data or panel data. The empirical results when using the two different approaches are compared.

The paper illustrates that the results from the pooled timeseries and cross section model could be biased for some basic implicit prices. With some nuances, it is illustrated that in specific situations the use of a basic panel data estimator could be a simple solution to the problem of misspecification due to omitted, time‐invariant explanatory variables.

Most of the included variables do not change over time, however. In these cases potential bias using a basic fixed effects approach could not be checked for. It is also problematic that the variation in some of the time‐varying variables is not reliable and small. Finally, there could be a problem with sample selection bias. This may limit the usefulness of using panel data in disaggregated hedonic house price studies.

Hedonic house price models are frequently used in housing market research. It is therefore important to study in various ways whether the traditional approaches provide unbiased results. In this paper models that use panel data are compared to models that use more traditional time series and cross section data. To the author's knowledge, this approach has not been followed before.

Renewable energy (RE) is an important component to the complex portfolio of technologies that have the potential to reduce CO₂ emissions and to enhance the security of energy supplies. Despite RE's potential to reduce CO₂ emissions, the expenditure on renewable energy research, development, and demonstration (RERD&D) as a percentage of total government energy research, development, and demonstration (ERD&D) investment remains low in developed countries. The declining ERD&D expenditure prompted this research to explore the relationship between CO₂ emissions per capita and RERD&D as opposed to ERD&D.

An econometric analysis of annual CO₂ emissions per capita during the period 1990‐2004 for the 15 pre‐2004 European Union (EU15) countries was carried out. It was hypothesized that the impact of RERD&D expenditure on the reduction of CO₂ emissions would be higher than that of ERD&D expenditure, primarily due to several RE technologies being close to carbon neutral. Country‐level gross domestic product per capita and an index of the ratio between industry consumption and industrial production were introduced in the analysis as proxies to control for activities that generate CO₂ emissions. A number of panel data econometric models that are able to take into account both country‐ and time‐specific unobserved effects were explored.

It was found that random effect models were more appropriate to examine the study hypothesis. The results suggest that expenditure on RERD&D is statistically significant and negatively associated with CO₂ emissions per capita in all models, whereas expenditure on ERD&D is statistically insignificant (ceteris paribus).

The findings of this paper provide useful insight into the effectiveness of RERD&D investment in reducing CO₂ emissions and are of value in the development of policies for targeted research, development, and demonstration investment to mitigate the impacts of climate change.

This study aims to empirically explore whether there is causality and in which direction, i.e. whether financial development generates economic growth or whether financial development merely follows economic growth in transition European countries, including Russian Federation and Turkey, during 1998-2015.

The study uses different techniques such as pooled OLS, fixed and random effects and the Hausman–Taylor model with instrumental variables.

The regression results show a positive relationship between financial development indicators and real GDP per capita growth, thus supporting the hypothesis that finance leads economic growth. The result also shows that financial crisis has a negative effect on real GDP per capita growth. Furthermore, these findings show that government spending and inflation have a negative impact on real GDP per capita growth. The study also shows that financial development plays growth-supporting role in real GDP per capita growth in 20 European countries in transition, including Russian Federation and Turkey.

As financial development generates real GDP per capita growth, on the basis of the results of the study, a course of action that involves institutional improvement and incentivizing competition in the financial sector is recommended to the Central Banks’ policymakers in transition economies. These will in turn lead to higher real GDP per capita growth.

The study is original in nature and makes effort to promote financial development in transition European countries, including Russian Federation and Turkey. The findings of this study will be of value to Central Banks and other policymakers.

This paper studies the dynamics and elasticities of house prices in Spain and Portugal (Iberia) at the Metropolitan Statistical Area (MSA) level, addressing panel regression problems such as heterogeneity and cross-sectional dependence between MSA.

The authors develop a two steps study. First, five distinct estimation methodologies are applied to estimate the long-term house price equilibrium of the Iberian MSA house market: Mean Group (MG), Fully Modified Ordinary Least Square (FMOLS) MG (FMOLS-MG), FMOLS Augmented MG (FMOLS-AMG), Common Correlated Effects MG (CCEMG) and Dynamic CCEMG (DCCEMG). FMOLS-AMG is found to be the best estimator for the long-term model. Second, an additional five distinct estimation methodologies are applied to estimate the short-term house price dynamics using the long-term FMOLS-AMG estimated price in the error-correction term of the short-term dynamic house price model: OLS Fixed Effects (FE), OLS Random Effects (RE), MG, CCEMG and DCCEMG. DCCEMG is found to be the best estimator for the short-term model.

The results show that in the long run Iberian house prices are inelastic to aggregate income (0.227). This is a much lower elasticity than what was previously found in US MSA house price studies, suggesting that there are other factors explaining Iberian house prices. According to our study, coastal MSA presents an inelastic housing supply and a price to income elasticity close to one, whereas inland MSA are shown to have an elastic supply and a non-significant price to income elasticity. Spatial differences are important and cross-section dependence is prevalent, affecting estimates in conventional methodologies that do not account for these limitations, such as OLS-FE and OLS-RE. Momentum and mean reversion are the main determinants of short-term dynamics.

Recent econometric advances that account for slope heterogeneity and cross-section dependence produce more accurate estimates than conventional panel estimation methodologies. The results suggest that house markets should be analyzed at the metropolitan level, not at the national level and that there are significant differences between short-term and long-term house price determinants.

To the best of the authors' knowledge, this is the first study applying recent econometric advances to the Iberian MSA house market.

Analyses Polish active labour market policy programmes (ALMP) from a macroeconomic (regional) point of view. The effects of training programmes on the outflows from unemployment into employment and the effects of all ALMP programmes on the outflows from employment into unemployment (to identify displacement effects) are estimated. The empirical evidence gives no support to the view that public training programmes can be used to reduce unemployment, and there is no robust evidence for displacement effects by any ALMP programme. The result that start‐up loans can reduce flows from employment into unemployment is only weakly significant.