Club convergence of crime rates in the United States of America

Purpose The cyclical behavior of US crime rates reflects the dynamics of crime in the country. This paper aims to investigate the US's club convergence of crime rates to provide insights into whether the crime rates increased or decreased over time. The paper also analyzes the factors influencing the probability of states converging to a particular convergence club of crime. Design/methodology/approach The analysis is based on balanced panel data from all 50 states and the district of Columbia on violent and property crime rates covering 1976–2019. This yields a cross-state panel of 2,244 observations with 55 time periods and 51 groups. In addition, the author used a club clustering procedure to investigate the convergence hypothesis in the study. Findings The empirical results support population convergence of violent crime rates. However, the evidence that supports population convergence of property crime rates in the study is not found. Further analysis using the club clustering procedure shows that property crime rates converge into three clubs. The existence of club convergence in property crime rates means that the variation in the property crime rates tends to narrow among the states within each of the clubs identified in the study. Analysis based on an ordered probit model identifies economic, geographic and human capital factors that significantly drive the state's convergence club membership. Practical implications The central policy insight from these results is that crime rates grow slowly over time, as evident by the convergence of violent crime and club convergence of property crime in the study. Moreover, the existence of club convergence of property crime is an indication that policies to mitigate property crime might need to target states within each club. This includes the efforts to use state rather than national crime-fighting policies. Social implications As crimes are committed at the local level, this study's primary limitation is the lack of community-level data on crime and other factors considered. Analysis based on community-level data might provide a better representation of crime dynamics. However, the author hopes to consider this as less aggregated data are available to use in future research. Originality/value The paper provides new insights into the convergence of crime rates using the club convergence procedure in the USA. This is considered an improvement to the methods used in the previous studies.

Club convergence and drivers of house prices across Turkish cities

PurposeThis paper aims to examine the convergence pattern of residential house prices in a panel of 55 major cities in Turkey over the period between 2010 and 2018 and to investigate the determinants of convergence club formations.Design/methodology/approachThe authors applied the log t-test to identify the convergence clubs and estimated ordered logit model to determine the key drivers.FindingsThe results suggest that there are five convergence clubs and confirm the heterogeneity of the Turkish housing market. Istanbul, the commercial capital, and Mugla, an attractive tourist destination, are at the top of the housing market and followed by the cities located in the western part, particularly along the Aegean and Mediterranean coasts of Turkey. Moreover, the ordered logit model results point out that the differences in employment rate, climate, population density and having a metropolitan municipality play a significant role in determining convergence club membership.Practical implicationsLarge-scale policy measures aiming to increase employment opportunities in rural cities of central and eastern provinces and providing lower land prices and property taxes in the metropolitan cities of Turkey can help mitigate some of the divergence in the house prices across cities.Originality/valueThe novelty of this study lies in employing a new data set at the city level containing 55 cities in Turkey, which is by far the largest in terms of city coverage among emerging market economies to implement the log t-test. It also contributes to the literature on city-specific determinants of convergence club formation in the case of an emerging economy.

Testing for Convergence in Competitiveness and Growth in Selected Economies from 1994 to 2020

Competitiveness on a small and large scale is necessary for growth. A definitive link between the level of competitiveness and growth has been difficult to prove. One of the primary objectives of economic planning is to promote price and exchange rate stability. Entrepreneurialism and productivity also increase the country’s export competitiveness. The aim of this study is to test for the convergence in competitiveness and convergence club existence in selected economies. No previous research had tested for convergence in competitiveness using a nonlinear timevarying factor model. This paper provides an overview on convergence in competitiveness and convergence clubs’ existence for 42 countries using quarterly data from 1994q1 to 2020q4 testing on competitiveness. Convergence log (t) test results show differences in competitiveness between classified convergence clubs. Russia, Brazil, and Turkey are the clubs (groups of countries) that show a transitional path (convergence in competitiveness) that differs entirely from the rest of the sample. Countries with more natural resources and exogenous monetary policies follow a unique development path to competitiveness. We find no evidence of divergence in countries within the clubs. However, we find a club (group of countries) following a clear divergence path from the other countries (Russia, Brazil, and Turkey). Our findings could potentially explain the increase in divergence in competitiveness across countries after the financial crisis of 2008.

Closer together or further apart? Club convergence in the Organization of Islamic Cooperation (OIC) countries

Purpose This paper aims to examine the per capita income convergence of 57 member countries of the Organization of Islamic Cooperation (OIC) over the period 1990–2017 and to investigate the determinants of convergence club formations. Design/methodology/approach The authors applied the methodology of Phillips and Sul (2007, 2009) to identify the convergence clubs and estimated several-ordered logit models to determine the key drivers. Findings The results support existence of two convergence clubs and one diverging unit, indicating that 30 and 26 member countries form two separate groups converging to their own steady-state paths. They also suggest a significant productivity divergence between these clubs. The authors showed that the number of convergence clubs started to decline after the global financial crisis in 2008. Moreover, they found that fixed capital formation, education and political stability are key drivers of convergence club membership. Practical implications There is a strong need for large-scale policy interventions to close the gap between leading and lagging clubs of the OIC. A substantial investment in human and physical capital seems necessary for lower-income OIC countries. Originality/value This is the first empirical study on the existence of convergence clubs among member countries of the OIC.

Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals

The aim of this paper is to test for overall and cluster convergence of housing rents across Polish provincial capitals and to identify drivers of convergence club formation. In order to achieve the goal of the study, several novel convergence tests were used, including the Kong et al. (J Econom 209:185–207, 2019. https://doi.org/10.1016/j.jeconom.2018.12.022) and Phillips and Sul (Econometrica 75:1771–1855, 2007. https://doi.org/10.1111/j.1468-0262.2007.00811.x) approaches. Moreover, club convergence analysis was carried out in four different configurations, varying in the technique of trend component extraction from the data. In particular, three well-known methods of time series decomposition were used, i.e. the Hodrick–Prescott, Butterworth and Christiano–Fitzgerald filters, as well as the most recent boosted Hodrick–Prescott filter. The results indicated that rental prices across the studied cities do not share a common path in the long run. It is possible, however, to identify convergence clubs where rents are moving towards a club-specific steady state. Detailed analysis of the structure of estimated clusters showed that data filtering using the boosted Hodrick–Prescott method leads to the most reliable allocation of cities to convergence clubs. Moreover, the estimation of logit models revealed that the likelihood of any two cities belonging to the same convergence club depends mainly on similar levels in terms of the unemployment rate, housing stock, city area, and the number of students. Finally, recommendations for local and national policy-makers concerning the development of the rental market have been formulated, particularly in the areas of urban land-use planning policy, housing legislation and public–private partnerships.

Economic Liberalization And Its Link To Convergence: Empirical Evidence From RCEP and TPPA Countries

Economic liberalization has been the emphasisof adjustment policies in developing countries; ASEAN countries jumped on the bandwagon and espousedeconomic reforms by liberalizingits international trade andfinancial policies. Through the development of free tradeagreement policies such as AEC and RCEP,regional economic integration is accelerating in South East Asia; not leaving behind the less developed member countries such as Cambodia, Lao PDR, Myanmar and Vietnam (CLMV). Hence, the objectives ofthis paper are to examine the dynamic impact of economic liberalization (financial and trade liberalization) on ASEAN’seconomic growth and to assess the possibility of the existence of convergence club between ASEAN and its RCEPcounterparts. Using the annual data covering the period of 1994to 2014, the analysis is based on the Pooled Mean Group (PMG) estimations for liberalization analysis while the Phillips and Sul (2007) methodology is used to assess the economic convergence clubs. The empirical evidence suggests that both trade and financial liberalization play a significant role in ASEAN’seconomic growth. For convergencein RCEP,full sample find an absence of homogenous convergence;as a result, four club convergencesare formed.The result highlights the importance of trade and financial liberalization in enhancing economic growth of ASEANandimpliesthat strong commitments in continuation of liberalization and integration policies arerecommended to promote a sustained economic growth.

The Impact of Globalization on The Ecological Footprint: Do Convergence Clubs Matter?

This paper investigates the impact of globalization on the ecological footprint for 130 countries over the period 1980-2016. To do so, we follow a two-step procedure. First, we analyze convergence in ecological footprint and identify possible convergence clubs across countries using a novel approach proposed by Phillips and Sul (2007). Then, we investigate the impact of globalization on ecological footprint using panel FMOLS (Fully Modified Ordinary Least Squares) and panel DOLS (Dynamic Ordinary Least Squares) methods. The results show that globalization is significantly and positively related to the ecological footprint both for the full panel sample and for all convergence clubs. However, the impact of globalization on ecological footprint significantly varies across convergence clubs and full panel sample. Furthermore, the findings show that the convergence club with the lowest impact of globalization on the ecological footprint is the closest club to the panel average.

Testování hypotézy konvergence v regionu střední Evropy pomocí kointegrace

The issue of regional disparities development is usually examined only in terms of beta- and sigma-convergence. To extend the discussion, therefore, it is needed to use approaches based on completely different principles, which are not burden with always the same methodological limits. In this context, the aim of this contribution is to apply the cointegration approach to assess the development of regional disparities in economic performance and income in Central Europe. On the sample of 62 regions in 2004-2018, this contribution applies the disparity evaluation method based on the Pesaran's probabilistic approach. In particular, we test the convergence hypothesis by KPSS test (null of stationary), and the divergence hypothesis by ADF test (null of unit root). The analysis found the regional convergence in economic performance, but not in income. After extending the analysis to the level of individual countries, internal regional convergence within most of countries was found in both economic performance and income. As part of the disparity evaluation in economic performance, "western" (regions of the Austria, Czechia and Germany) and the "eastern" convergence club (Hungary, Poland and Slovakia) were identified. Similarly, in the case of income analysis some signs of convergence club (Czechia, Hungary and Slovakia) were found.

Does High-Speed Railway Influence Convergence of Urban-Rural Income Gap in China?

Transportation is an important factor affecting the balance of regional economic pattern. The construction of high-speed railway enhances the mobility of population, capital, technology and information resources between urban and rural areas. Will it further affect the income gap between urban and rural areas? Based on the nonlinear time-varying factor model, this paper analyzes the convergence of urban-rural income gap with the angle of high-speed railway. After rejecting the assumption of overall convergence in the traditional four economic regions, three convergence clubs of urban-rural income gap were found. For these ordered logit regression model is used to explore the initial factors that may affect the formation of “convergence club”. Empirical results show that the construction of High-speed railway has effectively narrows the urban-rural income gap in China, but it is not the cause of the formation of the three convergence clubs. The convergence effect of High-speed railway on the urban-rural income gap in China is still relatively weak.