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Literature, spanning industrial organization and strategic management disciplines, uses variance decomposition to understand the relative importance of firm, industry and business group effects in shaping profitability variations. Some literature analyzes firm profitability under transition to liberalization. Previous research has taken a static before-and-after view on institutional change. This paper aims to focus on the dynamic process of liberalization in India, analyzing how different institutional regime changes alter firm behavior leading to changes in profitability patterns.

Based on a panel data set of several thousand Indian firms, spanning the 26-year period between 1980-1981 and 2005-2006, the authors determine the relative importance of firm, industry and business group effects in explaining manufacturing firms’ profitability variances across different institutional phases. The authors evaluate three propositions that help assess transition dynamics between phases. They determine the quantum of catch-up or falling behind by firms.

Different industries emerge as profitability leaders, as the economy progresses through different liberalization phases. Business groups that have been more effective in resource appropriation, rent-seeking, politician management and non-market activities in a controlled regime are replaced as profit leaders by those that, in a free-market economy, can be capable of intra-business resource allocation tasks and leveraging corporate capabilities.

The approach demonstrates how to analyze the underlying detailed structure of firm-level data, and performance outcomes, to derive nuanced interpretation of factors giving rise to the effects that explain profitability variances, and how to assess the way these effects behave over time. The dynamic evidence-based approach highlights what factors matter, where, when and why, in influencing profitability variances, which are a key dimension of industrial and economic performance.

To investigate the Central and Eastern European (CEE) equity market co‐movements before, during and after major emerging market crises. To examine the impact of the crisis on the gains of international portfolio diversification in CEE.

The study is based on the concept of co‐integration. The daily US dollar returns are analyzed for the period August 28, 1996 to August 2, 2001. The whole period is split into three sample periods. The first one is the pre‐crisis period from August 28, 1996 to May 30, 1997. The crisis period is from June 2, 1997 to January 31, 1999. The third period is the post‐crisis from February 1, 1999 to August 31, 2001.

Indicates no long‐run relationship between the US and the four Central European stock markets. Demonstrates a feedback effect and causality in one direction during and after the crisis period. Confirms a decrease of portfolio benefits in the crisis period and an increase of portfolio benefits in the post‐crisis period.

It is based on econometrics tests that quantify market integration and measure opportunities for international portfolio diversification. Employment of asset pricing models is viewed as a future research.

A very useful source of information for investors in Central and Eastern Europe.

One of the first papers investigated the benefits from portfolio investments in Central and Eastern Europe stock markets during financial crises.

The purpose of this paper is to present the growth trends in IT industry after the period of globalization in 1990s and to investigate the short-run and long-run dynamics between IT software and service exports, globalization and economic growth in India.

Annual time series data on IT exports, net national product and openness index have been collected from National Association of Software and Service Companies, the Reserve Bank of India database on Indian economy and the World Bank for the present study. The methodology adopted for studying the first objective are growth trend models, descriptive statistics and graphs prepared on the basis of data from the IT sector. Growth trends in key performance variables, such as total output, export, domestic output and employment have been analyzed. In the case of second objective, vector auto regression model has been used based on variance decomposition and impulse response function to capture the short-run and long-run dynamics between IT exports, globalization and economic growth in India.

Results of the growth trend model show the relative growth performance of software services receipts shows its strong advancement compared to the other sub-components of current account of balance of payments of India. It is found that economic growth responds positively to the shocks in IT exports and openness of economy. Further, IT software and service exports and openness index contribute to economic growth more in the long-run rather than in the short run.

The IT software and service exports is dynamic field of economic activity amid heavy dependence on both domestic and external economic and political environment; hence, the rate of change is so rapid, and the relevance of factors may change over time.

The paper has implications for achieving sustainability in IT software and service exports growth. It is recommended that economic growth can be enhanced by implementing policies that not only improve the efficiency of the sector but also focus on optimization of the potential of the Indian IT industry.

This paper focuses on originality in delineating the growth trends and analysis of capturing the short-run and long-run dynamics between IT exports, globalization and economic growth in India.

This study aims to examine the relationship between economic policy uncertainty and stock market liquidity in an order-driven emerging stock market.

Empirical estimates are based on vector autoregressive Granger-causality tests, impulse response functions and variance decomposition analysis.

The empirical findings suggest that economic policy uncertainty moderately influences stock market liquidity during normal market conditions. However, the role of economic policy uncertainty for determining stock market liquidity is significant in times of financial crises. The authors have also observed a significant portion of variation in stock market liquidity that is attributed to investor sentiments during financial crises.

This study is original in nature and provides evidence to consider economic policy uncertainty as a possible source of commonality in liquidity in the context of an emerging market.

This paper examines the short and long‐term comovements among UK regional property markets over the period 1976‐2001. The markets examined are London, Outer South East, East Anglia, South West, East Midlands, West Midlands, Yorkshire and Humberside, North and North West. Multivariate cointegration procedures, Granger non‐causality tests, level VAR and generalised variance decomposition analyses based on error‐correction and vector autoregressive models are conducted to analyse relationships among these markets. The results indicate that there is a stationary, long‐term relationship and a number of long‐term causal linkages between the various UK property markets. In terms of the percentage of variance explained, other regional markets are generally more important than innovations in a given region, though this is not the case for the Outer South East. The Outer South East market is segmented from the other regional markets, though also extremely influential in explaining forecast variance in these markets. The overall suggestion is that opportunities exist for portfolio diversification in the UK regional property market, and the Outer South East market should be seen as containing valuable information for forecasting performance in the regional markets.

The purpose of this paper is to examine the relationship between financial development indicators and human development in India using annual data from 1980-2012.

The Ng-Perron unit root test is used to check for the order of integration of the variables. The long run relationship and short run dynamics are examined by implementing the ARDL bounds testing approach to co-integration. Granger’s non-causality test and variance decomposition techniques are also used to examine the impact of financial development indicators on human development.

The results confirm a long run relationship among the variables. The results of granger non causality indicate that unidirectional causality runs from financial development indicators to human development index (HDI). The variance decomposition analysis shows that among all the financial indicators, broad money supply (M3) has the largest contribution to changes in human development in India.

The present study recommends for appropriate reforms in financial market to attain sustainable human development in India. The findings will be useful for India’s policy makers, in order to maintain the parallel expansion of financial development and human development.

This paper is first of its kind to empirically examine the casual relationship between financial development indicators and human capital development proxied by HDI in India by using modern econometric techniques.

The purpose of this paper is to examine the short‐ and long‐run causal relationship between energy consumption and gross domestic product (GDP) of six emerging economies of Asia. The importance of identifying the direction of causality emanates from its relevance in national policy‐making issues regarding energy conservation.

This paper employs co‐integration and vector error correction modeling along with generalized impulse response functions and varience decomposition tests to check the robustness of the findings.

The empirical results show that there exists unidirectional short‐ and long‐run causality running from energy consumption to GDP for China, uni‐directional short‐run causality from output to energy consumption for India, whilst bi‐directional short‐run causality for Thailand. Neutrality between energy consumption and income is found for Indonesia, Malaysia, and Philippines. Both the generalized variance decompositions and impulse response functions confirm the direction of causality.

These findings have important policy implications for the countries concerned. The results suggest that while India may directly initiate energy conservation measures, China and Thailand may opt for a balanced combination of alternative polices.

Many economists and social scientists are claiming that the increased demand for energy from developing countries like China and India is one of the major reasons for the energy price hikes in recent times. In this backdrop, it is justified to search causal relationship between energy consumption and national output (GDP) of some developing countries from Asia. Since the traditional bivariate approach suffers from omitted variable problems, this paper employs a trivariate demand side approach consisting of energy consumption, income and prices.

As specific objectives, we intend to: (1) measure the connectivity between the spillovers of returns from the financial and nonfinancial sectors of the Brazilian stock market; (2) estimate the spillovers of individual returns for each sector to identify periods of higher and lower profits over a period of around eight years; (3) investigate the existence of relationships between these repercussions between pairs of sectoral indices, evaluating how much each specific sector transfers to each other and the market as a whole and (4) examine whether the connectivity of the Brazilian stock market itself and future interest rates in the USA and Brazil as well as the risk of the Brazilian economy, were explanatory variables of the dynamics of interdependence in the returns of these indices.

With a daily series of closing prices of sectoral indices from March 3, 2015, until June 21, 2023, we researched eight of the most relevant sectoral indices on the São Paulo Stock Exchange (B3). With this data, we estimate the Diebold–Yilmaz spillover index and frequency decompositions of Barunik–Krehlik.

The conclusions indicate that there is an overall connection of 66% in the financial and nonfinancial sectoral indices, with a peak of 83%. The consumer, energy and public services sectors stand out as significant sources of primary spillovers. When we classified secondary effects into periods, we saw that the shocks dissipated as time passed and the returns of the commodity index remained resilient across all periods.

Our conclusions highlight the influence of three main factors in sectors with a high degree of connectivity: periods of increased uncertainty; negative externalities in post-crisis periods and the impact of financial news on market sentiment. We think this study provides information that can be useful for policymakers, investors, investment portfolio managers, economists (financial, monetary and industrial), investment consultants and researchers who are interested in the complex interconnection among emerging market stock indices.

The purpose of this study is to find the empirical causal relationship between Islamic bank term deposit rates (IBTDR) and conventional bank term deposit rates (CBTDR) in the short-term.

This study analyzes the short-term causal relationship between the term deposit rates (TDRs) for the time period of three years 2015 to 2018 on monthly data of IBTDR and CBTDR. Granger causality test, variance decomposition and impulse response function are applied to examine if there is any short-term causal relationship between the IBTDR and CBTDR.

This empirical study establishes that the IBTDR are dependent on the CBTDR in the short-term.

This research provides an insight for the customers of TDRs of the Islamic banking system. This study is not only a significant insight for the end-users but also for the regulators and researchers as it provides important empirical evidence. This could lead to further research on the reasons for causality.

There has not been any study of this nature in Pakistan to identify the causality of the two-TDRs. This research expands the dynamics of research in the context of the banking sector.

Following Ang and Piazzesi’s (2003) study, the authors use an affine term structure model to study the relevance of macroeconomic (domestic and foreign) factors for Peru’s sovereign yield curve in the period from November 2005 to December 2015. The paper aims to discuss this issue.

Risk premia are modeled as time-varying and depend on both observable and unobservable factors; and the authors estimate a vector autoregressive model considering no-arbitrage assumptions.

The authors find evidence that macro factors help to improve the fit of the model and explain a substantial amount of variation in bond yields. However, their influence is very sensitive to the specification model. Variance decompositions show that macro factors explain a significant share of the movements at the short and middle segments of the yield curve (up to 50 percent), while unobservable factors are the main drivers for most of the movements at the long end of the yield curve (up to 80 percent). Furthermore, the authors find that international markets are relevant for the determination of the risk premium in the short term. Higher uncertainty in international markets increases bond yields, although this effect vanishes quickly. Finally, the authors find that no-arbitrage restrictions with the incorporation of macro factors improve forecasts.

To the authors’ knowledge this is the first application of this type of models using data from an emerging country such as Peru.