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In this article, we provide new, novel evidence for a more recent structural break (in 2010) indicating a greater moderation of output volatility compared to the well-known break during the mid-1980s. The period of analysis runs from 1962Q2 to 2018Q3. It covers 26 OECD countries. In terms of methodology, it has mainly been used as the measures of conditional and unconditional volatility and procedures of structural break detection (Inclan–Tiao test and autoregressive conditional heteroscedasticity model). As a result, it has been found that output greatly stabilized following the structural break at 2010Q1 in the post-era of 2008/09 global financial crisis. Moreover, output stabilization is robustly evident for 24 (out of 26) OECD countries. From a political standpoint, it is implied that the Keynesian view may be influential in this moderation. Government expenditures and fiscal programs, regulations of financial markets against the sub-prime lending and limitations to trade of mortgage-backed securities might have been the main driver of stability. Rapid improvement of digitalization and technical productivity may be regarded as another relevant reason that might have contributed to the stabilization process. © 2019, The Author(s).

The aim of the present article is to analyze the convergence of regional inflation rates in Turkey from 2004 to 2015 by adopting a distribution dynamics approach, namely discrete time Markovian chains. Convergence across regional inflation rates is politically a crucial matter for two reasons. First, if inflation rates differ largely between regions, monetary policy can hardly satisfy the needs of all regions equally. Such that, places which experience high inflation rates naturally require a contractionary monetary policy while the ones which experience low inflation need rather an expansionary monetary stance. Second, inflation differentials are likely to create a regional dispersion in real interest rates which induce differential effects on local economic growth. The outcomes of our research can be summarized in two groups. First, inflation disparities have declined over time, especially during the post-crisis period; after 2010. Hence, aggregate price stabilization and disinflation process in Turkey is coupled with convergence in inflation rates across regions. These results are confirmed using several methodologies (panel unit root tests and Kernel Density Estimates). Second, in addition to the findings in the literature, we found that regions change their relative inflation rate positions quite often. This indicates that regional inflation behaivor is random and non-structural as the relatively high and low inflationary places tend to change their quintiles frequently in time. Similarly, a geographical randomness of inflation is also verified using Moran I's test.

AbstractThe linearity of the distribution of city sizes is often assumed in the existing literature. Although different functional forms were tried, almost all of them impose a certain functional shape. In this study, we investigate the urban hierarchy and Zipf's law using data for 973 Turkish subprovincial cities in 2019. We contribute to the literature in several ways. We force no definite functional form to observe the natural shape and employ nonparametric and quadratic regressions. We incorporate formal procedures of spatial dependence in regression models. We demonstrate that the linear model overestimates the Pareto exponent for small cities and underestimates it for bigger cities. We show that city sizes are unevenly distributed in Turkey. The rank–size rule is not valid in Turkey, either above or below a certain city‐size truncation level. Thus, the Pareto exponent estimated from the linear model is not a reliable indicator as quadratic regressions perform much better.

AbstractThe purpose of the current study is to investigate the degree of inflation persistence, its geographical variation, sources of cross‐regional variation, and presence of geographical/sectoral aggregation bias in national monetary policy. Our data set covers 26 NUTS‐2 level Turkish regions and monthly CPI inflation over the period 2003–2019. We first estimate the degree of regional inflation persistence by autoregressive regressions, check its robustness against the presence of structural breaks (by Bai–Perron's algorithm) and nonlinearities (by Markovian Regime Switching regressions). Second, we examine the possibility of geographical and sectoral aggregation bias. Third, we investigate the cross‐regional determinants of inflation persistence by panel data analysis, employing hybrid‐effects spatial panel regressions. We analyze the direct and indirect effects of the determinants and test for regional spillover effects. Three main results are obtained. First, estimated persistence degrees are heterogeneous across regions. The geographical pattern is empirically robust against structural breaks and nonlinearities. We find that inflation persistence is distributed in a spatially correlated manner. Second, when sectoral and regional aggregation bias is tested, only sectoral aggregation indicates a considerable level of bias. Third, we find that the presence of large firms in the region and a higher share of agricultural output in GDP leads to lower persistence, while an increased share of industrial output, and increased trade volume leads to higher inflation persistence. Moreover, we find spatial spillovers of price variability evident in regression analysis. From a policy standpoint, it is required that structural policy programs are targeted to maintain flexibility in the regions where persistence is high (i.e., providing market entry/exit, institutional quality, policy credibility, stimulation of SMEs). Moreover, sectors that have high persistence, such as Hotels and Restaurants (persistence degree 0.55) and Health Services (0.39) should be weighted more in CPI calculations.

AbstractThe presence of cycles characterizes all economic systems, but economic cycles have differentiated spatial impacts. Some regions have broader cycles with respect to the country, while others tend to be less responsive to shocks and hence have narrower cycles. Being exposed to broader cycles, that is, greater volatility, may increase the strain on a regional economic system. This paper investigates the different responsiveness to cyclical forces and volatility of regions in the long run. It does so by using quarterly employment data for the Nuts2 Italian regions over almost 40 years before and during the period 1978–2016. Explored in particular are the cross‐regional variations in employment volatility and the reasons for the patterns observed, as well as whether they have changed the following different macroeconomic policy regimes. The paper identifies the break dates of different regimes, and these regime changes will be related to policy modifications, such as the implementation of the European Monetary Union. The determinants of this regional volatility appear to be quite stable, so that the changes in volatility are explained by how these determinants have changed overtime and how they are unevenly distributed in space. In particular, the lagging regions of the country suffer, in addition to lower production and income, from higher volatility due to a structure which is weaker and more unstable. Volatility can hence be an additional issue for lagging regions.

AbstractThis paper aims to improve the shortcomings of the empirical literature on regional social capital. The following three research questions are addressed: (i) do regional social capital and economic growth have an endoneous (circular) relationship as opposed to the exogenous one‐way relationship assumed in the literature; (ii) What are the socio‐economic and demographic determinants of cross‐regional variation in social capital? And (iii) Are spatial spillovers relevant in the analysis of these questions? Empirically, we pursue the analysis for 81 Turkish provinces in 2015. Indeed, regional social capital in Turkey is far less studied than country‐level social capital. The methodology adopted includes kernel density estimates, ordinary least squares, three stage least squares, and spatial error models. In terms of the obtained results, First, regional social capital is heterogenously distributed across regions. Second, social capital has no significant impact on economic growth but the growth induces the generation of social capital (in social norms). This represents a first result of reserve causality in the literature. Third, a typical province that has high social capital is the one with relatively high income, more even income distribution, low unemployment, big households and older age profile. Fourth, there is the evidence of spatial dependence that should be incorporated in empirical analyses.

In this paper we study business cycle correlations in the Eurozone and its determinants. Additionally, we also analyze the determinants of the lead and lag behavior of business cycles in the Eurozone. We explore the relevance, in the Eurozone context, using GDP and employment as the business cycle measures, of the determinants of business cycle synchronization identified in the literature, namely bilateral trade intensity, dissimilarity of labor market rigidity, dissimilarity in industrial structures, financial openness, and foreign direct investment relations. We estimate a simultaneous 4-equations model by Ordinary Least Squares (OLS) and three-stage least square to investigate empirically the above-mentioned determinants of business cycle correlation. Bilateral trade relations present a positive influence on business cycle correlations, while the dissimilarity of labor market rigidity presents a negative influence. The rest of the above-mentioned variables are non-significant. These results are robust to the use of the Hodrick–Prescott-filter and first differences as the de-trending methods, as well as the use of GDP as the business cycle measure, excluding the financial crisis years (2008 and 2009). Results for employment as the business cycle measure are in contrast with the previous ones, and found industrial dissimilarity to be the relevant variable to determine business cycles synchronization. In what concerns the determinants of the lead and lag behavior, results show that the member states of the Eurozone that usually lead the cycle are the ones that are wealthier, with strict employment legislation, more specialized in construction and finance sectors, and more prone to international capital movements. Differences in the determinants between contemporaneous business cycles and lead and lag behavior of business cycles are especially important for policy-makers in the Eurozone to know about, in particular if asymmetric shocks between countries are set in place. ; Fundacao para a Ciencia e Tecnologia (UID/GES/00315/2013)