Nadir Öcal

MILITARY EXPENDITURE AND ECONOMIC GROWTH IN MIDDLE EASTERN COUNTRIES: A DYNAMIC PANEL DATA ANALYSIS

Defence expenditures have both costs and benefits to the economy. The costs of defence expenditures are mainly emphasized as opportunity costs. On the other hand, defence spending may have growth‐promoting potential benefits: a rise in defence spending may result in a higher aggregate demand, production and employment. This paper examines empirically the effects of military expenditures on economic growth for Middle Eastern countries and Turkey, for the time‐period 1989–1999. The relationship between military expenditure and economic growth is investigated by using cross‐section and dynamic panel estimation techniques. Empirical analysis indicates that military expenditure enhances economic growth in the Middle Eastern countries and Turkey as a whole.

Asymmetric Interest Rate Effects for the UK Real Economy

Recent literature has uncovered asymmetries in the response of real output to monetary policy variables. Nevertheless, it remains unclear whether such asymmetries relate to different responses to monetary policy or to the business cycle. This paper uses nonlinear models to examine the issues in the context of interest rate effects on quarterly UK GDP growth. Strong evidence of nonlinearity is found, with asymmetry relating to the business cycle through lagged GDP regimes and interest rate changes. The results suggest that interest rate effects on GDP are larger when either lagged growth has been high or when interest rates have substantially increased in the past. However, the inclusion of interest rate regimes without taking account of GDP regimes yields an unsatisfactory model.

Regional effects of terrorism on economic growth in Turkey: A geographically weighted regression approach

The economic growth effects of terrorism have generally been examined in a cross-country framework where socio-economic differences among the countries are ignored. This highly restrictive assumption may result in heterogeneity bias, which could be overcome by resorting to country studies rather than cross-country analysis. Moreover, the relationship between the terrorist incidents and various factors may not be stationary in space. The majority of terrorist incidents in Turkey are concentrated mainly in Eastern, and South Eastern Turkey and big cities. Thus, the geographical dispersion of terrorist incidents in Turkey may result in uneven regional impact, necessitating local parameter estimates. This study analyses the effects of terrorism on economic growth across provinces of Turkey for the time period 1987—2001. Following a traditional global regression analysis, spatial variations in the relationships are examined with geographically weighted regression (GWR) to obtain locally different parameter estimates. A GWR approach allows the modeling of relationships that vary over space by introducing distance-based weights to provide parameter estimates for each variable and each geographical location. Empirical evidence indicates that a GWR model significantly improves the model fitting over the traditional global model. Even though the traditional convergence analysis reveals that terrorism hinders economic growth, GWR results indicate that its provincial effects are more pronounced for the Eastern and South Eastern provinces compared to the Western provinces. Moreover, empirical findings suggest that there is a considerable variation in speeds of convergence of provinces, which cannot be captured by the traditional beta convergence analysis.

Income Inequality and Economic Convergence in Turkey: A Spatial Effect Analysis

Even though the convergence of regional per capita income has been a highly debated issue internationally, empirical evidence regarding Turkey is limited as well as contradictory. This article is an attempt to investigate regional income inequality and the convergence dynamics in Turkey for the time period 1987—2001. First, the Theil coefficient of concentration index is used to analyze the dispersion aspects of the convergence process. The geographically based decomposition of inequality suggests a strong correlation between the share of interregional inequality and spatial clustering. Then, we estimate convergence dynamics employing alternative spatial econometric methods. In addition to the global models, we also estimate local models taking spatial variations into account. Empirical analysis indicates that geographically weighted regression improves model fitting with better explanatory power. There is considerable variation in speed of convergence of provinces, which cannot be captured by the traditional beta convergence analysis.

ARMS RACE AND ECONOMIC GROWTH: THE CASE OF INDIA AND PAKISTAN*

The hostility between India and Pakistan is believed to have led to an arms race between the two countries, which might have contributed to their retarded economic growth. This paper investigates this twin problem of arms race and economic growth for the time period 1949–2003. The empirical results suggest that there is a mutual causal relationship between the military expenditures of India and Pakistan. Even though military expenditure does not Granger cause economic growth in Pakistan, there is causality from military expenditure to economic growth in India. A VAR analysis revealed that military expenditure hinders economic growth in India in the long‐run, but it has a growth promoting effect in the short‐run. *An earlier version of this paper has been presented at the Seventh Annual International Conference on Economics and Security held in Bristol, UK, on 26–28 June 2003.

ANALYSING THE DETERMINANTS OF TERRORISM IN TURKEY USING GEOGRAPHICALLY WEIGHTED REGRESSION

This paper investigates the determinants of provincial terrorism in Turkey taking spatial dimension into account for the time period 1990–2006. Following a traditional global regression analysis, spatial variations in the relationships are examined with geographically weighted regression (GWR) to obtain locally different parameter estimates. Empirical results indicate that increases in income and schooling ratio tend to reduce the provincial average level of terrorism, whereas an increase in unemployment enhances it. Moreover, GWR results indicate that the provincial effects of per capita income and education are more pronounced for the Eastern and South Eastern provinces compared to the Western provinces.

Are the military expenditures of India and Pakistan external determinants for each other: An empirical investigation

Empirical modeling of arms race between India and Pakistan has been a focus of interest in many studies. Nevertheless, the possibility of asymmetric dynamics between the variables under question seems to be ignored in these studies. The purpose of this paper is to fill this gap of the earlier literature by examining possible asymmetric effects of military expenditures of India and Pakistan on each other. It is assumed that asymmetry is due to the existence of two distinct regimes characterizing the variable of interest, with regime shift being a function of either a past value of the dependent or an exogenous variable. Smooth transition class of nonlinear models is used in the study. The results for Pakistan indicate that Indias military expenditure have more deep effects when the past military expenditure of Pakistan is high, implying asymmetric relationship between the two variables.

Military expenditures, economic growth and spatial spillovers

The relationship between economic growth and military expenditure has been the subject of a large literature in defence economics. This study analyses the influence of military expenditures on economic growth in a global perspective for the time period 2000–2010 taking spatial dimension into account. The augmented Solow model is employed to investigate the defence-growth nexus using the cross-sectional data relating to 128 countries. Following a traditional regression analysis, spatial variations in the relationships are examined utilizing different spatial econometric specifications estimated by maximum likelihood. The regressions are compared with each other via likelihood ratio tests, and the spatial Durbin model is found to be the most appropriate one suggesting that the typical least-squares model is misspecified. Empirical evidence indicates that military expenditure has a positive effect on economic growth with a significant spatial dependence for the time period under consideration.

Asymmetric effects of military expenditure between Turkey and Greece

One of the major topics of the defense economics literature regarding Turkey and Greece has been the empirical modeling of various aspects of arms racing. However, despite a considerable amount of research, little evidence has been found in favor of an arms race between the two countries. In the literature, this failure of applied studies has been attributed, among other reasons, to the sensitivity of the results to the underlying model specification, to small sample size, and to measurement issues. This study uses novel, nonlinear, models to investigate the possible relationship between the military expenditures of the two countries. It is assumed that if there are two regimes characterizing the low (or negative) and high-growth military expenditure periods, the growth rates of one countrys military expenditure may have distinct effects on the military expenditure regimes of the other country or may contribute to the change from one regime to another. The nonlinear models examined are Smooth Transition Regression models (STRs). Strong evidence of nonlinearity for Greece is found, with asymmetry relating to two distinct regimes through lagged Turkish military expenditure changes.

Nonlinear models, composite longer leading indicator and forecasts for UK real GDP

This paper examines the role of the Office for National Statistics Composite Longer Leading Indicator, in nonlinear business cycle models for growth rates of UK real gross domestic product (GDP). These models are of the smooth transition regression class, with the transition between “regimes” expressed as functions of lagged changes in the leading indicator. In general, evidence is found of business cycle regime asymmetries, with increases and decreases in the leading indicator implying distinct responses for the dependent variable. Single transition function appears to capture these asymmetries satisfactorily. Nonlinear models provide more accurate one-step ahead forecasts than corresponding linear leading indicator models.