A publication titled “Time-frequency comovement among green bonds, stocks, commodities, clean energy, and conventional bonds” on Finance Research Letters by Thi Thu Ha Nguyen, Faruk Balli, Hatice Ozer Balli and co-authors in May 2021

Abstract

The paper examines the inter-relationship between green bonds and other asset markets, including stocks, commodities, clean energy, and conventional bonds over 11 years from 2008 to 2019. The dynamic features of correlation across asset pairs over time and in different frequencies are assessed through the rolling window wavelet correlation approach. We find strong evidence that most correlation emerged and reached a peak in the aftermath of GFC 2007-2009. While comovement among stocks, commodities, and clean energy is found relatively high, the diversification benefit of green bonds is significantly revealed due to its low or negative correlation with stocks and commodities.

A publication titled “Does weather, or energy prices, affect carbon prices?” on Energy Economics by Martin Young and co-authors in April 2021

Abstract

This study investigates the extent that key energy prices (coal, gas, oil and electricity) and weather explain carbon prices, a key feature of the European Union Emissions Trading Scheme (EU ETS), and whether this relationship changed since full auctioning came into effect in 2013. Energy prices were found to impact the carbon price in phase III of the EU ETS. However, modelling based solely on energy prices explained only 12% of carbon price variation. Weather variables did not affect the carbon price except for unanticipated temperature changes. These results indicate that it is not the level of temperature that impacts the carbon price, rather it is unanticipated changes in temperature that matter. Given that climate change is associated with increased variance in temperature, this result is consistent with climate change resulting in greater carbon price volatility and higher hedging costs.

A publication titled “Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets” on Energy Economics by Hung Do and co-authors in October 2020

Abstract

This study investigates the volatility connectedness between the Irish and Great Britain electricity markets and how it is driven by changes in energy policy, institutional structures and political ideologies. We assess various aspects of this volatility connectedness including static (unconditional) vs dynamic (conditional), symmetric vs asymmetric characteristics between 2009 and 2018. We find that the volatility connectedness is time-varying and it is significantly affected by important events, policy reforms or market re-designs such as Brexit, oil price slump, an increasing share of renewables, and fluctuations in the exchange rates. Our asymmetric analysis shows that magnitude of the good volatility connectedness is marginally larger than that of the bad volatility connectedness. Our result suggests that good volatility levels would be even higher once the Irish market adopts the carbon price floor. Therefore, supporting renewable generation by setting an appropriate price of carbon in interconnected wholesale electricity markets will improve market integration.

A publication titled “Exploiting the heteroskedasticity in measurement error to improve volatility predictions in oil and biofuel feedstock markets” on Energy Economics by Hung Do and co-authors in February 2020

Abstract

We examine whether heteroskedasticity in measurement errors improves the volatility forecasting ability of the Heterogenous Autoregressive (HAR) model in crude oil and biofuel feedstock markets. We also examine the incremental explanatory power of jumps and the investor fear gauge (IFG) over heteroskedasticity in measurement errors in improving the volatility forecasting ability of the HAR model in each of these markets. For the in-sample evaluation, we find that exploiting the heteroskedasticity of measurement errors in the HAR model improves the model’s goodness of fit (measured by adjusted R²) by up to 10% depending on the market. IFG has a significant incremental role over heteroskedasticity in measurement errors in improving the fit of the HAR model in both the crude oil and biofuel feedstock markets, while jumps have a significant incremental role in improving the fit of the HAR model in the crude oil market, but not the biofuel feedstock markets. For the out-of-sample forecasts, including regime switching improves volatility predictions in the corn and wheat markets across all forecasting horizons, while for the soybean market, including regime switching improves the performance of multi-step volatility forecasts. In the out-of-sample forecasts the best ranked models almost always include heteroskedasticity of measurement error and IFG.

A publication titled “The geography of CSR” on International Review of Economics & Finance by Jeff Wongchoti and co-authors in January 2019

Abstract

We regress socio-economic indicators against firm level CSR scores using a sample of over 26,000 firm year observations from 1991 through 2009. We find that a firm’s CSR profile is linked to the socio-economic conditions of the firm’s geographic headquarters (HQ) location. The study documents that the legal, cultural, economic, and demographic differences across geography significantly explain the variation in CSR means between metropolitan statistical areas, states, and regions. We also find that the relation between CSR and firm performance is conditional on socio-economic factors, which highlight the endogeneity concerns inherent in CSR studies. Lastly, we show that firms that cluster along a CSR continuum experience an increase in firm value.

A publication titled “Impact of gender and governance on microfinance efficiency” on Journal of International Financial Markets, Institutions and Money by Hatice Ozer Balli and co-authors in March 2018

Abstract

This study examines the efficiency of South Asian microfinance institutions (MFIs) using Data Envelopment Analysis. Bias corrected efficiency estimates for the individual MFIs are regressed on a set of explanatory variables (including governance and gender) employing the double bootstrap truncated regression approach (Simar and Wilson, 2007) and panel data regression. First stage results suggest that South Asian MFIs are more financially efficient than socially efficient. More precisely, we find that these MFIs are technically inefficient but scale efficient, and that there was some improvement in financial efficiency over time. The relatively low average efficiency scores show that there is quite a bit of variation in microfinance efficiency. Second stage regression reveals that female loan officers are positive determinants of MFIs’ efficiency. We find a strong association between a MFI’s governance and its financial and social efficiency.

A publication titled “New approaches to measure the social performance of microfinance institutions (MFIs)” on International Review of Economics & Finance by Hatice Ozer Balli and co-authors in January 2018

Abstract

Outreach is a central purpose of microfinance institutions in providing access to quality financial services for large numbers of poor people. This paper critically reviews outreach indicators for microfinance institutions from prior research using a South Asian panel data set covering the period 1998 to 2013. We introduce two new ways of measuring the social objectives of MFIs, reflecting market shares, for breadth and depth of outreach. The results show that these new outreach indicators provide a better explanation of social performance of MFIs than those commonly used in prior research.

A publication titled “Does it pay to be different? Relative CSR and its impact on firm value” on International Review of Financial Analysis by Jeff Wongchoti and co-authors in October 2016

Abstract

Conventional aggregation of Corporate Social Responsibility (CSR) raw scores and its interpreted impact on firm value have provided mixed evidence in the literature. We show that the value impact of CSR activities relies heavily on the industry-specific relative position of the firm. Only firms that distinguish themselves over their peers are associated with increased firm value. This finding is robust and holds for both responsible and irresponsible behaviors. Information concerns and portfolio construction can allude to a possible CSR clientele, suggesting the existence of an optimal CSR level. Our peer-effect results are robust to unobserved heterogeneity along the lines of Gormley and Matsa (2013).