Tracing the causes of the banking crisis

We add the Bernanke–Gertler–Gilchrist model to a modified version of the Smets–Wouters model of the U.S. in order to explore the causes of the banking crisis. The innovation of this article is estimating the model using unfiltered data allowing for non-stationary shocks in order to replicate how the model predicts the crisis. We find that ‘traditional shocks’ account for most of the fluctuations in macroeconomic variables; the non-stationarity of the productivity shock plays a key role. Crises occur when there is a ‘run’ of bad shocks; based on this sample they occur on average once every 64 years and when they occur around 10% are accompanied by financial crisis. Financial shocks on their own, even when extreme, do not cause crises – provided the government acts swiftly to counteract such a shock as happened in this sample.     

Coupling urban expansion models and hydrological models: How important are spatial patterns?

It is well known that urban expansion has a severe impact on the surface water balance by transforming vegetated covers into sealed surfaces. This transformation causes changing fluxes of evapotranspiration, surface runoff and groundwater recharge. In order to estimate the impact of land cover changes on the surface hydrology, hydrological models are often coupled with different types of land cover change models. It is, however, not clear to what extent spatially-explicit urban expansion scenarios provide an added value in comparison with non-spatial urban expansion models at different scale levels. The objective of this paper is to acquire a better insight in the importance of scale effects involved in the coupling of urban expansion scenarios and hydrological models. The relative importance of using different projections of both (i) quantity and (ii) spatial patterns of urban expansion was analysed at four different scale levels. The highly urbanised Flanders–Brussels region was taken as an example application. Twelve different urban expansion scenarios for 2025 and 2050 were developed and subsequently used as an input in a spatially-distributed water balance model. The results obtained suggest that at the level of the Flanders–Brussels region, an accurate estimation of the quantity of urban expansion should get priority over an accurate projection of the spatial patterns. However, the importance of using accurate projections of the spatial pattern of urban expansion increases systematically at local scale levels. A uniform strategy for coupling urban expansion models and hydrological models thus seems inappropriate. These findings are highly relevant for water management and spatial planning policymakers that typically operate at different administrative levels.     

Fractional cointegration and futures hedging

This article examines the performance of various hedge ratios estimated from different econometric models: The FIEC model is introduced as a new model for estimating the hedge ratio. Utilized in this study are NSA futures data, along with the ARFIMA-GARCH approach, the EC model, and the VAR model. Our analysis identifies the prevalence of a fractional cointegration relationship. The effects of incorporating such a relationship into futures hedging are investigated, as is the relative performance of various models with respect to different hedge horizons. Findings include: (i) Incorporation of conditional heteroskedasticity improves hedging performance; (ii) the hedge ratio of the EC model is consistently larger than that of the FIEC model, with the EC providing better post-sample hedging performance in the return–risk context; (iii) the EC hedging strategy (for longer hedge horizons of ten days or more) incorporating conditional heteroskedasticty is the dominant strategy; (iv) incorporating the fractional cointegration relationship does not improve the hedging performance over the EC model; (v) the conventional regression method provides the worst hedging outcomes for hedge horizons of five days or more. Whether these results (based on the NSA index) can be generalized to other cases is proposed as a topic for further research. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 457–474, 1999     

Determinants of bilateral trade: evidence from ASEAN+3

In this research, we investigate the determinants of international trade, employing a dataset of bilateral trade and economics characteristics in the ASEAN+3 countries. We include a large number of independent variables that potentially drive international trade. We also use various standard gravity model variables to maintain consistency with the current literature. The results provide some important insights into the determinants of bilateral trade and offer policy implications regarding the promotion of international trade for governments worldwide. In particular, we find that output asymmetry between countries positively explains bilateral trade. Moreover, the findings suggest that making use of comparative advantage by differentiating the export product structure is important in promoting international trade. We do not find a consistent impact from bilateral exchange rate volatility on bilateral trade. This result points to the importance of providing opportunities for the hedging of currency uncertainty to avoid its adverse effects on trade. The results for other standard gravity model variables are consistent with the results of previous theoretical and empirical research.     

Volatility and Price Jumps in Agricultural Futures Prices—Evidence from Wheat Options

Evidence suggests that agricultural futures price movements have fat-tailed distributions and exhibit sudden and unexpected price jumps. There is also evidence that the volatility of futures prices is time-dependent both as a function of calendar-time (seasonal effect) and time to maturity (maturity effect). This article extends Bates' (1991) jump-diffusion option pricing model by including both seasonal and maturity effects in the volatility specification. Both in-sample and out-of-sample procedures to fit market option prices on wheat futures show that the suggested model outperforms previous published models. A numerical example shows the magnitude of pricing errors for option valuation.     

Liquidity and Return Relationships in an Emerging Market

In this paper, we investigate the relationship between liquidity and stock returns in the Vietnam stock market during the global financial crisis. Vietnam is one of a new group of frontier emerging markets referred to as CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa). We use a rich and detailed data set of firm characteristics to identify a positive relationship between liquidity and stock returns. This contradicts the negative correlation typically found in stock returns in developed markets. Our results support the proposition that when a market is not fully integrated with the global economy, a lack of liquidity will be a less important risk factor. Our findings contribute to those studies that highlight the diversification benefits from including frontier markets, which have a lower degree of integration with the global economy, in international portfolios.     

Regional differences in the production processes of financial and social outputs of microfinance institutions

This study uses panel data of microfinance institutions across the world to compare production processes across regions, assess the relevance of unobserved heterogeneity and estimate economies of scale. Comparing a financial production process to a multidimensional production process that accounts for the presence of outreach in the objective function suggests that financial and social output reflect complements in South Asia but not in other regions. Furthermore, we find substantial economies of scale for a pure financial production process. However, accounting for outreach lowers estimated economies of scale, suggesting that producing outreach creates high transaction costs and requires exploitation of local knowledge.