Most studies of exchange rate exposure of stock returns do not address three relevant aspects simultaneously. They are, namely: sensitivity of stock returns to exchange rate changes; sensitivity of volatility of stock returns to volatility of changes in foreign exchange market; and the correlation between volatilities of stock returns and exchange rate changes. In this paper, we employ a bivariate GJR-GARCH model to examine all such aspects of exchange rate exposure of sectoral indexes in Japanese industries. Based on a sample data of fourteen sectors, we find significant evidence of exposed returns and its asymmetric conditional volatility of exchange rate exposure. In addition, returns in many sectors are correlated with those of exchange rate changes. We also find support for the "averaged-out exposure and asymmetries" argument. Our findings have direct implications for practitioners in formulating investment decisions and currency hedging strategies.

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In this paper we argue that the commonly employed exposure coefficient/beta is inadequate to capture the entire impact of exchange rate changes on firms' future operating cash flows. Instead, we employ the bivariate GJR-GARCH-M models to investigate four aspects of exchange rate exposure, including sensitivity of stock returns to exchange rate changes, sensitivity of stock returns to the volatility of exchange rate changes, sensitivity of conditional variance of returns to exchange rate volatility, and the dynamic conditional correlation between returns and exchange rate changes, respectively, using data from ten industrial sectors in Japan. We find significant evidence of such exchange rate exposure which is not captured by the conventional measure. The diagnostic statistics confirm the adequacy of our model, and hence the robustness of the results.

Purpose While sustainable development policies are mostly set based on United Nations (UN) geoscheme classification, no study attempts to examine the impact of influential economic variables such as energy consumption (EC) and merchandise exports (ME) on carbon dioxide (CO2) emission in the UN geoscheme regions. The purpose of this paper is to examine the possible impact of EC and ME on CO2 emission in UN geoscheme classification regions such as Africa, America, Arab, Asia and Europe. Design/methodology/approach This paper uses autoregressive distributed lag (ARDL), Pedroni panel cointegration and panel Granger causality methodologies covering an annual panel data sampling period from 1971 to 2014. Findings The results show that there is bidirectional causality between all three variables in the European and American panel except for the non-causality from CO2 to EC in the American panel. These findings suggest possible consequences of weaker energy efficiency (even under environmental policy tightening) and strong demand for energy-intensive economic activities in those regions. Developed countries with higher environmental policy tightening (America and Europe) show significant estimates from the chosen tests supporting the Porter hypothesis. EC and ME have a long-run impact on CO2 emission in American and European panels. The African region has the least environmental impact of pollution from ME. Practical implications The ME and EC have a direct significant impact on CO2 emission in America and Europe. As these causalities, co-integrations and their impacts share a long-run equilibrium relationship, policymakers must design long-term industry policies such as cleaner production techniques focusing on environmentally sustainable practices. Also, it is suggested that the policymakers must ensure that they implement more robust policies and standards for environmental-friendly export production. Originality/value This is the first paper that examines the impact of EC and ME on CO2 emission in UN geoscheme regions. The findings of this paper provide theoretical implications supporting Porter hypothesis and practical implications for policymaking.

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The objective of this study is to identify the short and long-run determinants of inflation in Sri Lanka. It follows an eclectic approach to seeking possible determinants of inflation and employs an Autoregressive Distributed Lag (ARDL) bounds testing approach to test for co integration between inflation and its causes. The findings indicate that increased money supply, depreciation of the rupee and higher public wages are the major causes of inflation in both the short and long-run. Thus, it can be stated that inflation in Sri Lanka is affected by both demand and supply side factors, which highlights the importance of a prudent and effective implementation of the monetary and fiscal policies so as to ensure a stable macroeconomic environment in Sri Lanka.

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