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Article
Publication date: 5 August 2019

Vaseem Akram and Badri Narayan Rath

The purpose of this paper is to examine the convergence analysis of public debt among Indian states using annual data from 1990‒1991 to 2014‒2015.

Abstract

Purpose

The purpose of this paper is to examine the convergence analysis of public debt among Indian states using annual data from 1990‒1991 to 2014‒2015.

Design/methodology/approach

The paper tests this hypothesis using club convergence technique propounded by Phillips and Sul (2007).

Findings

The results reveal the existence of debt divergence for overall Indian states. States are formed into four clubs on the basis of their level of debt, and three clubs support the hypothesis of club convergence. Further, the total public debt decomposes into three compositions such as market loans, bank loans and loans and advances from the central government. The existence of convergence is found for market loans and bank loans; however, the presence of divergence is found in case of loans and advances for overall states.

Practical implications

Since public debt plays an important role for fiscal health of the Indian states, findings of this study suggest to squeeze the fiscal consolidation further for Indian states whose debts as a percentage to gross state domestic product are on the higher side. Further, the examination of debt convergence helps to manage debt level among the states because heavy dependence on public debt could retard investment and economic growth.

Originality/value

Whereas bulk of empirical studies emphasize on examining the linkage between public debt and economic growth, and issue on debt sustainability across Indian states, examination of convergence of debt and its compositions (markets borrowings, bank loans and loans and advances from the central government) among the Indian states is scanty.

Details

Journal of Economic Studies, vol. 46 no. 4
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 26 February 2020

Vaseem Akram, Pradipta Kumar Sahoo and Badri Narayan Rath

This paper investigates the per-capita output club convergence in case of 120 countries for the period 1995–2015. Further, we disaggregate per-capita output into three…

Abstract

Purpose

This paper investigates the per-capita output club convergence in case of 120 countries for the period 1995–2015. Further, we disaggregate per-capita output into three broad sectors such as agriculture, industry, and service and investigate the convergence hypothesis.

Design/methodology/approach

The paper tests this hypothesis using the Phillips and Sul panel club convergence technique.

Findings

Our findings are as follows: (1) our results indicate the evidence of output divergence for the full sample; (2) when countries are divided into different clubs, the results exhibit the sign of per capita output club convergence both for aggregate and three major sectors. Further, this study confirms that industry's per capita output is the main driver for aggregate per-capita output club convergence in case of club 1. For club 2, agriculture's per capita output is a primary source for aggregate per capita output club convergence. Likewise, in the case of clubs 3 and 4, we find the service sector's per capita output is the main component for aggregate per-capita output club convergence; (3) both the service and industry sectors are major drivers for aggregate per-capita output club convergence.

Practical implications

This study suggests to the policymaker that sector-specific policies need to be adopted to boost the per-capita output growth by improving the performance of each of the sectors across the countries.

Originality/value

Notwithstanding, there are many studies that examine the output convergence using a notion of beta and sigma convergence, but studies regarding per capita output club convergence both at the aggregate and sectoral level are scanty.

Details

Journal of Economic Studies, vol. 47 no. 4
Type: Research Article
ISSN: 0144-3585

Keywords

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Book part
Publication date: 15 April 2020

Jianning Kong, Peter C. B. Phillips and Donggyu Sul

Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key…

Abstract

Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key economic indicators. Econometric methods, known as weak σ-convergence tests, have recently been developed (Kong, Phillips, & Sul, 2019) to evaluate such trends in dispersion in panel data using simple linear trend regressions. To achieve generality in applications, these tests rely on heteroskedastic and autocorrelation consistent (HAC) variance estimates. The present chapter examines the behavior of these convergence tests when heteroskedastic and autocorrelation robust (HAR) variance estimates using fixed-b methods are employed instead of HAC estimates. Asymptotic theory for both HAC and HAR convergence tests is derived and numerical simulations are used to assess performance in null (no convergence) and alternative (convergence) cases. While the use of HAR statistics tends to reduce size distortion, as has been found in earlier analytic and numerical research, use of HAR estimates in nonparametric standardization leads to significant power differences asymptotically, which are reflected in finite sample performance in numerical exercises. The explanation is that weak σ-convergence tests rely on intentionally misspecified linear trend regression formulations of unknown trend decay functions that model convergence behavior rather than regressions with correctly specified trend decay functions. Some new results on the use of HAR inference with trending regressors are derived and an empirical application to assess diminishing variation in US State unemployment rates is included.

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Article
Publication date: 14 June 2019

Nicholas Apergis and James E. Payne

The purpose of the study is to examine the long-run convergence properties of condominium prices based on the ripple effect for five major US metropolitan areas (Boston…

Abstract

Purpose

The purpose of the study is to examine the long-run convergence properties of condominium prices based on the ripple effect for five major US metropolitan areas (Boston, Chicago, Los Angeles, New York and San Francisco). Specifically, we test for both overall convergence in condominium prices and the possibility of distinct convergence clubs to ascertain the interdependence of geographically dispersed metropolitan condominium markets.

Design/methodology/approach

Our analysis uses two approaches to identify the convergence properties of condominium prices: the Lee and Strazicich (2003) unit root test with endogenous structural breaks and the Phillips and Sul (2007, 2009) time-varying nonlinear club convergence tests.

Findings

The Lee and Strazicich (2003) unit root tests identify two structural breaks in 2006 and 2008 with the rejection of the null hypothesis of a unit root and long-run convergence in condominium prices in the cases of Boston and New York. The Phillips and Sul (2007, 2009) club convergence test reveals the absence of overall convergence in condominium prices across all metropolitan areas, but the emergence of two distinct convergence clubs with clear geographical segmentation: on the east coast with Boston and New York and the west coast with Los Angeles and San Francisco while Chicago exhibits a non-converging path.

Research limitations/implications

The results highlight the distinct geographical segmentation of metropolitan condominium markets, which provides useful information to local policymakers, financial institutions, real estate developers and real estate portfolio managers. The limitations of the research are the identification of the underlying sources for the convergence clubs identified due to the availability of monthly data for a number of potential variables.

Practical implications

The absence of overall convergence in condominium prices, but the emergence of distinct convergence clubs that reflects the geographical segmentation of metropolitan condominium markets raises the potential for portfolio diversification.

Originality/value

Unlike previous studies that have focused on single-family housing, this is the first study to examine the convergence of metropolitan area condominium prices.

Details

International Journal of Housing Markets and Analysis, vol. 12 no. 6
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 29 April 2020

James E. Payne

This survey of the literature on the convergence of carbon dioxide (CO2) emissions informs researchers on areas for future research by summarizing the countries examined…

Abstract

Purpose

This survey of the literature on the convergence of carbon dioxide (CO2) emissions informs researchers on areas for future research by summarizing the countries examined, the types of convergence tested and the methodological approaches undertaken.

Design/methodology/approach

This survey examines peer-reviewed empirical studies of CO2 emissions convergence with respect to country coverage and alternative approaches to test for various types of convergence.

Findings

For large multicountry studies, the support for convergence is quite limited. However, studies focused exclusively on a subset of countries defined by income classification, geographic region or institutional structure reveal the finding of convergence is more prevalent. Studies at the subnational level have primarily been in the cases of the US and China with the exception of two studies across industry sectors in Portugal and Sweden.

Research limitations/implications

This study focuses exclusively on peer-reviewed published studies.

Practical implications

This study is relevant to the design of mitigation strategies to reduce CO2 emissions and the assumption of convergence underlying climate change models.

Social implications

As a major component of greenhouse gas emissions, CO2 emissions is of global importance in its impact on the environment and climate change.

Originality/value

This study provides the most recent and comprehensive survey of the empirical literature on the convergence of CO2 emissions.

Details

Journal of Economic Studies, vol. 47 no. 7
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 11 December 2019

Bhushan Praveen Jangam, Pradipta Kumar Sahoo and Vaseem Akram

The purpose of this study is to examine whether the electricity consumption patterns across Indian states do converge.

Abstract

Purpose

The purpose of this study is to examine whether the electricity consumption patterns across Indian states do converge.

Design/methodology/approach

This study considers 18 Indian states spanning over the period 1970-1971 and 2014-2015, using the recently developed Phillips and Sul panel convergence technique that accounts the multiple steady states.

Findings

The results provide the following insights. First, the authors find evidence of convergence in electricity consumption among all Indian states. This suggests that electricity consumption patterns for Indian states are converging to a common steady state. Second, to provide broader insights, we further investigate the convergence in electricity consumption among user groups such as agriculture, industry, commercial, domestic and miscellaneous. The results reveal that commercial, domestic and miscellaneous groups are also converging. Third, the non-convergence patterns in agriculture and industry enable us to investigate the possibility of clubs or the multiple common steady states. The results indicate the occurrence of three clubs in case of agriculture and two clubs in case of the industry. Fourth, this study also inspects the relative speed of convergence among the user groups. The results reveal the higher speed of convergence in case of the domestic user group.

Practical implications

The findings enable policymakers to formulate an appropriate energy policy to accommodate the future electricity demand across Indian states and prioritize low electricity consumption states so that they receive a greater share.

Originality/value

This is the first study that examines the convergence in electricity consumption across Indian states at aggregate and user groups using a new panel club convergence technique.

Details

International Journal of Energy Sector Management, vol. 14 no. 3
Type: Research Article
ISSN: 1750-6220

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Article
Publication date: 28 October 2014

Nicholas Apergis, Christina Christou and Christis Hassapis

This paper aims to explore convergence of accounting standards across worldwide adopted measures to investigate whether countries that have not completely adopted…

Abstract

Purpose

This paper aims to explore convergence of accounting standards across worldwide adopted measures to investigate whether countries that have not completely adopted International Accounting Standards across the globe have displayed a tendency to act so.

Design/methodology/approach

The new panel convergence methodology, developed by Phillips and Sul (2007), is employed.

Findings

The empirical findings suggest that countries form distinct convergent clubs, albeit on a limited prevalence, yielding support to the notion that on a global basis firms and countries have initiated processes that will eventually lead them to a uniform pattern of employing common accounting standards.

Practical implications

These findings have substantial implications on a firm level, mainly for differences in accounting quality as well as for differences in their cost of capital, thus leading the regulatory authorities to opt for further improvements in financial reporting.

Originality/value

The novelties of this paper first, stem from the fact that it is the first time in the relevant literature that an empirical study attempts to formally measure whether the accounting world exhibits a tendency for accounting standards convergence or whether tactics and policies remain stagnant, acquiring drastic policy measures to speed up the convergence process. In addition, this study employs the implementation of the new methodology of panel convergence testing. This methodology has several appealing characteristics.

Details

Accounting Research Journal, vol. 27 no. 3
Type: Research Article
ISSN: 1030-9616

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Book part
Publication date: 21 November 2014

John Chao, Myungsup Kim and Donggyu Sul

This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial…

Abstract

This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial condition. The new estimators we introduce are weighted averages of the well-known first difference (FD) GMM/IV estimator and the pooled ordinary least squares (POLS) estimator. The proposed procedure seeks to exploit the differing strengths of the FD GMM/IV estimator relative to the pooled OLS estimator. In particular, the latter is inconsistent in the stationary case but is consistent and asymptotically normal with a faster rate of convergence than the former when the underlying panel autoregressive process has a unit root. By averaging the two estimators in an appropriate way, we are able to construct a class of estimators which are consistent and asymptotically standard normal, when suitably standardized, in both the stationary and the unit root case. The results of our simulation study also show that our proposed estimator has favorable finite sample properties when compared to a number of existing estimators.

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Article
Publication date: 8 June 2021

Lokman Gunduz, Hamad Mohammed Rahman Humaid Alshamsi and Mehmet Yasin Ulukus

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…

Abstract

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.

Details

International Journal of Islamic and Middle Eastern Finance and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8394

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Book part
Publication date: 21 November 2014

Ryan Greenaway-McGrevy, Chirok Han and Donggyu Sul

This paper is concerned with estimation and inference for difference-in-difference regressions with errors that exhibit high serial dependence, including near unit roots…

Abstract

This paper is concerned with estimation and inference for difference-in-difference regressions with errors that exhibit high serial dependence, including near unit roots, unit roots, and linear trends. We propose a couple of solutions based on a parametric formulation of the error covariance. First stage estimates of autoregressive structures are obtained by using the Han, Phillips, and Sul (2011, 2013) X-differencing transformation. The X-differencing method is simple to implement and is unbiased in large N settings. Compared to similar parametric methods, the approach is computationally simple and requires fewer restrictions on the permissible parameter space of the error process. Simulations suggest that our methods perform well in the finite sample across a wide range of panel dimensions and dependence structures.

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