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Previous studies demonstrate that market-oriented reform has contributed significantly to China's economic growth from the efficiency-based economic view. But some argue that state-owned firms have access to policy information, scarce resources, and government support, and thus state-owned firms might foster innovation. This study tries to find out either market force or state ownership helps improve firms' R&D efficiency.

Using data from China's high-tech industry, we employed the fixed-effect stochastic frontier model and the spatial panel Han-Philips linear dynamic regression model to investigate the relationship between market-oriented reform and the dynamic evolution of R&D efficiency in both temporal and spatial dimensions. Moreover, we examined whether the relationship is affected in a state-owned economy and an industry protection environment.

The results indicate the following: (1) the R&D efficiency of China's high-tech industry has improved steadily and has converged gradually across its regions during the market-oriented reform; (2) the marketization degree is positively correlated with R&D efficiency and its regional convergence; (3) the state-owned economy and industry protection have significantly weakened the ability of market forces to shape R&D efficiency — i.e. they reduce, rather than enhance, R&D efficiency.

This investigation helps understand the drivers of R&D efficiency in transition economies, and the findings are also helpful in defining the boundaries and constraints of market forces.

Based on the approach of Timljonavich and Vogelsang, the purpose of this paper is to present empirical evidence of the role of the federal transfers on the β‐convergence process in Canadian provinces.

The paper uses information on annual personal income for the period 1926‐1999 to present empirical evidence about the notion of β‐convergence for the ten Canadian provinces.

The principal conclusion is that the inter‐provincial transfers were not determinant or decisive to the attainment of deterministic convergence in the Canadian provinces.

While the issue of convergence has been analyzed especially using cross‐sectional data or panel data, this paper uses a time‐series methodology with statistics recently proposed by Vogelsang and Bunzel, which are robust to the presence of I(0) or I(1) disturbances.

The purpose of this paper is to answer one important question: in the aftermath of a systemic banking crisis, can the expected deviations in credit supply, liquidity, and other bank characteristics become entrenched in that they do not converge back to “normal”?

Using a panel data set of commercial banks in the Mercosur during the period 1990-2006, the authors analyze the impact of crises on four sets of financial indicators of bank behavior and outcomes – profitability, maturity preference, credit supply, and risk taking. The authors employ convergence methodology – which is often used in the growth literature – to identify the evolution of bank behavior in the region after crises.

A key finding of the paper is that bank risk-taking behavior is significantly modified leading to prolonged reduction of intermediation to the private sector in favor of less risky government securities and preference for high levels excess liquidity well after the crisis. This can be attributed to the role played by macroeconomic and institutional volatility that has nurtured a relatively high level of risk aversion in banks in the Mercosur.

To the best of the authors’ knowledge, using convergence methodology is a relatively novel approach in this area. An added advantage of using this approach over others currently used in the literature is that the authors can empirically quantify the rate of convergence and the institutional and macroeconomic factors that condition the convergence. Moreover, the methodology allows one to identify – in some hierarchical order – factors that condition persistent deviation from “normality.” The lessons learned from the Mercosur case study are useful for countries that suffered systemic banking crises in the aftermath of the global financial crisis.

The purpose of this study is to examine the role of institutions and policies on growth convergence in Africa.

This study uses different methods of panel modelling on a panel of 50 African Countries covering a period of 1990-2014.

The results confirmed the presence of conditional convergence among countries in the region. On the average, technology accumulation and fiscal policies indicators are positive function of growth, while human resources, monetary policies indicators and ineffective institutions partly necessitated by poor level of development negatively impact growth. The study concludes, though traditional growth variables and policies are imperative in achieving growth in income, they remain insufficient in an environment characterize by extractive and absolutist institutions. Therefore, institution remains the link that bridges the gap in between proper mix of resources and policies.

Based on the results, policy-makers in the region should allocate certain percentage of their resources (on a sustainable basis) towards building a qualitative institution. Also, future studies on Africa should be focused on the rate at which poor level of economic development determines the quality of institutions which in turn impacts the level of growth in income.

The study contributes to the existing literature on institutional convergence with particular focus on African countries using system GMM to capture the endogeneity among the series.

In this chapter, I attempt to extend insights regarding statistical aggregates from scholars, such as Hayek (1931) and Mises (1947), to the topic of inequality. Using the work of Lindert and Williamson (2016), I show that a disaggregation of inequality into some of its many subcomponents alters our reading of its evolution. While I only work with stylized facts from the field of economic history, and the authors argues that the promising implications derived from disaggregation militate in favor of more effort being directed toward decomposing the evolution of inequality.

The purpose of this paper is to investigate the food price inflation convergence across countries and regions. This study aims to identify the key drivers for food price inflation across countries and regions.

We test whether the international food price inflations are converging over time using the log t convergence test and clustering analysis. These inflation data are collected from the Food and Agriculture Organization of the United Nations.

The test results suggest that there is little evidence of overall convergence. Then we utilize a clustering algorithm and the results support that there is strong evidence of multiple convergence clubs. In addition, we examine the transition path of the various convergence and find that social stability regulation together with economic conditions are important determinants of convergence club membership.

First off, local conflict and economic environment result in food supply and prices, but this study is limited to the dynamics of prices.

Food prices inflations are not converging to single common price inflation, but there exist subgroups of countries or regions within which food price inflation tends to converge. These groupings tend to be related to the economic development and social stability of countries and regions.

The authors believe that any analysis of food price inflations that does not consider the political environment and economic conditions dynamics will likely be omitting important components of food price dynamics.

This study uses a unique data set covering 198 countries and regions and provides a comprehensive analysis of international food price inflation convergence identifying the key drivers of convergence club membership.

The four Asian tigers, Hong Kong, Singapore, South Korea and Taiwan (also called Four Dragons) experienced miraculous high growth rates in the pre-1990s period and rapidly transformed their economic status from less developed “basket cases” to developed high-income countries gaining entry to the rich OECD club of countries. These countries even in the post-1990s, barring few years, have continued to grow further and are an inspiring role model for the newly emerging economies. The purpose of this paper is to adduce certain trends in these countries since the 1990s and specifically examine role of human capital and knowledge building, productivity convergence and intra-regional trade in the Asian tigers’. The authors examine these in the context of India.

The paper in a simple descriptive yet analytical approach explores the relevance of above factors in the Indian context.

The study observed that India ranks far below the Asian tigers in the knowledge economy index (KEI). The results at the sub-national level showed large disparities across the states in knowledge economy reflecting country’s difficulties in catching up with other countries overall. Regarding labour productivity, the results show that India was moving away from the benchmark country until 1990 (pre-reform period) and started catching up particularly due to physical capital (not necessarily human capital) since 1995 onwards.

The study is unique due to several reasons. First, it contributes to the literature examining contemporaneous Asian tigers and Indian economies performance as not many studies exist in this area. Second, the study also builds a unique first ever KEI at the sub-national level for India and is, therefore, a contribution in this respect. Finally, the study also contributes to the literature on Indian economic development.

The purpose of this paper is to investigate convergence hypothesis in a balanced panel of 22 Indian states for the time period of 1980-81 to 2010-11 by applying nonparametric model setting in a panel framework.

The present study uses nonparametric and semi-parametric panel data methods to test the absolute and conditional convergence, respectively, and examines the income convergence using nonparametric panel data methods with state specific effects taken into consideration. These models are being estimated by the iterative process for a balanced panel of state wise per capita income and other conditioning variables for the time period of 1980-81 to 2010-11. For removing the fixed effects, the authors follow within transformation procedure according to the feasibility of the problem. Since convergence is estimated by regressing dependent variable on initial level of independent variable (as growth rate of income and per capita income in this case). So using usual transformation for removing the fixed effects is not feasible because by doing so the authors may end up with singular matrices on both sides of the regression model.

The results reject the null of parametric specification for both absolute as well as conditional convergence model. As to the outcome of the empirical analysis, the findings reveal that the Indian states are diverging in absolute sense and converging on conditional basis. Convergence happens to be consistent and conditional upon public expenditure, power generation share of primary and tertiary sector to Gross State Domestic Product.

The originality of the study is in its application of advanced methodology to highlight the model misspecifications while testing the convergence hypothesis in earlier literature.

This paper aims to investigate the impact of knowledge spillover effects (KSE) on employment levels using a sample of 245 Italian Innovative startup companies created as a result of the legislative changes of Law Decree 179/12 introduced in Italy in 2012.

This study uses a parsimonious model with the employment level as the dependent variable. The paper tests for the impact that the measures of industry competition, specialization and diversity have on the level of employment in the Innovative Startup sector in Italy. The data uses a sample of 245 firms, across 20 geographic regions in Italy for three economic sectors at the 2-Dig NAICS classification.

The empirical results provide evidence in favor of regional specialization as the main force to create and transfer knowledge resulting in increased employment; while higher levels of competition and a more diverse regional production bases result in lower firm employment levels. Employment levels for these firms are also time-dependent, and thus mainly determined at the time of the firm’s creation. This study also found a lack of technological convergence across regions, that are inherent regional differences are not bridged by knowledge spillover effects.

This paper is based on a sample of Italian Innovative Startups and consequently, further research with a potentially larger sample and, perhaps, a sample across countries could also shed some light on the issues relating to KSE and their effects on employment generation and firm formation.

From a practical point of view, the results indicate that regional disparity and limited transmission of KSE across regions remain an impediment to the flow of knowledge. This in turn may limit the development of entrepreneurial activities and further development of new firms. Practical implications regarding knowledge management indicate that firms face time and spatial challenges when developing, transferring and acquiring knowledge. In sum, the evidence points out in favor of existent and persistent regional heterogeneity in terms of economic and technological specialization as sources of employment.

This research adds to the empirical evidence focusing on the effects of knowledge spillover effects in the Innovative Startup segment of the economy. This research highlights the applicability of knowledge spillover effects accounting for levels of industry competition, specialization and diversity. We also provide a measure of cluster formation and concentration at the sectoral and regional levels. Thus, the research provides a better understanding under which conditions knowledge is more likely to have positive or negative effects on employment generation.

This paper aims to examine the integration of housing markets in Canada by examining housing price data (1999–2016) of six metropolitan areas in different provinces, namely, Calgary, Vancouver, Winnipeg, Toronto, Montreal and Halifax. The authors test for cointegration, driver cities of long-run relationships, long-run Granger causality and instantaneous causality in light of the global financial crisis (GFC) (2007–2008).

The authors use Johansen’s system cointegration approach with structural breaks. Moving average representation is used for common stochastic trend(s) analysis. Finally, the authors apply vector error correction model-based Granger causality and instantaneous causality.

Cities’ housing prices are in long-run equilibrium. Post-crisis Canadian housing markets became more integrated. The Calgary, Vancouver, Toronto and Montreal markets drive the Canadian housing market, leading all cities toward long-run equilibrium. Strong long-run Granger causality exists, but the authors observe no instantaneous causality. Price information takes time to disseminate, and long-run price adjustments play a significant role in causation.

The findings of cointegration increasing after the GFC and strong lead–lag can be used by investors to arbitrage and optimize portfolios. This can also help national and local policymakers in mitigating risk. Incorporating these findings can lead to better price forecasting.

This study presents many novelties for the Canadian housing market: it is the first to use repeat-sales regional pricing indices to test long-run behaviors, conduct common stochastic trend analyzes and present causality relations.