This study examines the effect of capital structure and firm quality on firm value of selected BSE listed Indian hospitality firms over a time frame of 2001-15. Variables including firm quality measured through Altman Z score, leverage, size, profitability, tangibility, growth, liquidity along with macro variables of growth in gross domestic product and inflation are taken into consideration for examining their impact on firm value. An empirical study has been carried out through panel data techniques by applying pooled OLS, fixed effects and random effects models. The findings of the study reveal a significant relationship of firm value with firm quality, leverage, liquidity, size and economic growth. The study shows that Modigliani miller theorem of capital structure irrelevance does not hold for Indian hospitality sector. It is of practical significance for hotel owners to reassess their capital structure to improve firm quality and firm's market performance.

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The determinants and stability of money demand functions, as per new definitions of monetary aggregates, has been analyzed in this paper. Quarterly Data from 1996Q2 to 2009Q2, for various monetary aggregates, interest rates, exchange rates, stock prices and GDP is in use. The cointegration tests, error correction mechanism, Granger causality and CUSUM tests has been applied for empirical analysis. The estimated results disclose the existence long-run and short-run relationship among the variables. Unidirectional Granger causality found from GDP and Stock Prices to monetary, new monetary as well as liquidity aggregates. Also similar result repeated from interest rates to money demand functions. The CUSUM and CUSUMQ tests support the existence of stability of each money demand functions. All the three variables, except exchange rate, affect the money demand of both types of specification.

Energy poverty plagues the sub‐Saharan Africa (SSA) region and impedes its socio‐economic development. It is impossible to attain sustainable‐development without alleviating energy‐poverty. In this study, we examine the role of governance and renewable‐energy in alleviating energy poverty for 22 SSA countries from 2000 to 2018 using system generalised method‐of‐moments and three‐stage least‐squares models. Government expenditure is found to increase economic growth, which in turn, reduces energy poverty. On the other hand, energy poverty is found to initially increase and then fall with rising renewable‐energy share. Additionally, the association of energy poverty with socio‐economic, environmental and governance factors, is analysed within a structural‐equation modelling (SEM) framework. Our SEM model shows that government institutional‐factors remain central to reducing energy poverty without compromising environmental‐sustainability. This study suggests that SSA needs transparent governance, strong institutions and a rising renewable‐energy share along with a resilient grid infrastructure to address the energy poverty problem.

The paper deals with forecasting international tourists footfalls in India, applying an assortment of uni-variate time series forecasting models, for monthly data spreading over Dec 1990 to Jan 2010. The forecasting performance of various competing models is evaluated with MAPE and other criteria. Also the actual and forecasted values are compared since Feb 2010 to Sept 2010 for better evaluation. The SARIMA model performs better than other competing model for forecasting, with lowest MAPE value. In fact it has an advantage over other models as it explicates autoregressive and moving average process not only for the data series but also of seasonality. As a policy implication, SARIMA model can be used for forecasting tourists demand in India.