On the nonlinear relationship between energy use and CO2 emissions within an EKC framework: Evidence from panel smooth transition regression in the MENA region

This paper proposes a new approach for analyzing the dynamic relationships between carbon dioxide (CO₂) emissions, energy use, and income for the Middle East and North African (MENA) region. Our study implements a class of regime-switching models, namely a nonlinear panel smooth transition regression (PSTR) framework. Two kinds of estimates for carbon emissions are provided. On the one hand, we measure the impact of energy consumption on CO₂ concerning the level of income per capita, as countries with a similar energy usage level would have different levels of energy intensity. On the other hand, we estimate the impact of output growth on emissions concerning energy usage variation, as a higher economic growth does not necessarily mean energy-intensive activities. Our empirical findings support these intuitions as they indicate that pollutant emissions respond nonlinearly to energy consumption and GDP growth. We find an inverted U-shaped pattern for the impact of energy on CO₂, in the sense that environmental degradation is declining beyond a given income threshold, which is estimated endogenously within the PSTR model. Also, our results underscore that GDP growth significantly impacts carbon emissions only for higher energy consumption growth.     

Current accounts and oil price fluctuations in oil-exporting countries: The role of financial development

Oil-exporting countries usually experience large current account improvements following a sharp increase in oil prices. In this paper, we investigate this oil price-current account relationship on a sample of 27 oil-exporting economies. Relying upon the estimation of panel smooth transition regression models over the 1980–2010 period, we provide evidence that refines the traditional interpretation of oil price effects on current accounts. While current accounts are positively affected by oil price variations, this effect is nonlinear and depends critically on the degree of financial development of oil-exporting economies. More specifically, oil price variations exert a stronger impact on the current account position for less financially developed countries, this influence diminishing with financial deepness.     

Bank-based versus market-based financial systems: A growth-theoretic analysis

We study bank-based and market-based financial systems in an endogenous growth model. Lending to firms is fraught with moral hazard as owner-managers may reduce investment profitability to enjoy private benefits. Bank monitoring partially resolves the agency problem, while market-finance is more ‘hands-off’. A bank-based or market-based system emerges from firm-financing choices. Neither system is unequivocally better for growth, which crucially depends on the efficiency of financial and legal institutions. But a bank-based system outperforms a market-based one along other dimensions. Investment and per capita income are higher, and income inequality lower, under a bank-based system. Bank-based systems are also more conducive for broad-based industrialization.     

A closer look at financial development and income distribution

This paper analyzes the under-investigated relationship uniting financial development and income distribution. We use a novel approach taking into account for the first time the specific channels linking banks, capital markets and income inequality, the time-varying nature of the relationship, and reciprocal causality. We construct a set of annual indicators of banking and capital market size, robustness, efficiency and international integration. We then estimate the determinants of income distribution using a panel Bayesian structural vector autoregressive (SVAR) model, for a set of 49 countries over the 1994-2002 period. We uncover a significant causality running from financial sector development to income distribution. In addition, the banking sector seems to exert a stronger impact on inequality. Finally, the relationship appears to depend on the characteristics of the financial sector, rather than on its size.     

Impact of the stock market capitalization and the banking spread in growth and development in Latin American: A panel data estimation with System GMM

This research is aimed at assessing the impact of the stock market capitalization and the banking spread in per capita economic growth (as a proxy of economic development) in the major Latin American economies during period 1994–2012. To do this, a panel data model is estimated with both system and difference Generalized Method of Moments. The main empirical findings are that economic growth in the countries under study is positively impacted by the stock market capitalization and negatively by the banking spread. Typical problems of multicollinearity and autocorrelation appearing in panel data analysis are corrected under the proposed methodology.     

The long-term role of non-traditional banking in profitability and risk profiles: Evidence from a panel of U.S. banking institutions

The goal of this empirical study is to identify empirically and on a panel basis how non-traditional bank activities affect directly the profitability and risk profiles of the financial institutions involved in such activities. Through a dataset that covers 1725 U.S. financial institutions involved in non-traditional bank activities spanning the period 2000–2013 and the methodology of panel cointegration, the empirical findings document that non-traditional bank activities exert a positive effect on both the profitability and the insolvency risk. The results could be important for regulators given they could serve as a pre-warning signal that sends a clear message to regulators about the potential systemic risk that exists within the financial markets.     

Openness and the finance-growth nexus

Rajan and Zingales (2003) hypothesize that openness—trade and financial—is a crucial determinant of financial development. The main policy implication emerging from this hypothesis is that openness should be promoted as a means of facilitating economic growth through financial development. While subsequent research confirms that openness affects financial development, we study whether finance continues to be growth promoting as economies become increasingly open—a key implicit assumption behind the policy recommendation. Using data from 78 economies for the period 1981–2006, we find that very high levels of financial openness generally erode the growth-promoting role of financial development while high trade openness strengthens it. These worldwide findings by and large hold for subsamples of Sub-Saharan African, Latin American and OECD economies. Notable exceptions are the invariance of the finance-growth (FG) nexus on trade openness in OECD economies and the positive effect of financial openness on the FG link in Latin American economies.     

A tale of two cities: Economic development,corporate governance and firm value in Vietnam

This study examines the moderating effect of financial and economic development on the relation between corporate governance and firm value in Vietnam, which has two exchanges, one located in the business center in the South, and the other located in the center of government in the North. This unique setting allows an investigation of corporate governance dynamics controlling for legal jurisdiction. The results show a positive relation between corporate governance and firm value in Ho Chi Minh City but not in Hanoi. The finding suggests that financial and economic development play critical roles in enhancing the benefits of corporate governance in emerging markets.     

Volatility and covariation of financial assets: A high-frequency analysis

Using high frequency data for the price dynamics of equities we measure the impact that market microstructure noise has on estimates of the: (i) volatility of returns; and (ii) variance–covariance matrix of n assets. We propose a Kalman-filter-based methodology that allows us to deconstruct price series into the true efficient price and the microstructure noise. This approach allows us to employ volatility estimators that achieve very low Root Mean Squared Errors (RMSEs) compared to other estimators that have been proposed to deal with market microstructure noise at high frequencies. Furthermore, this price series decomposition allows us to estimate the variance covariance matrix of n assets in a more efficient way than the methods so far proposed in the literature. We illustrate our results by calculating how microstructure noise affects portfolio decisions and calculations of the equity beta in a CAPM setting.