Social networks and small business performance in West African border regions

This paper studies the links between economic performance and social networks in West Africa. Using data collected on 358 small-scale traders in five border markets, we show that social networks can be simultaneously a resource which positively contributes to labour market outcomes and a social burden that has a negative economic impact. Testing the effect of social networks between small traders and three categories of actors, we find that the most well-connected actors are also the most successful in terms of monthly profit. The effects of social networks are, however, dependent on the type of persons with whom traders are connected. We show that support received from state representatives and politicians is converted into economic performance, while the impact of law enforcement officers on the monthly profits of traders is not significant. We also find that interacting with traditional religious leaders has a negative effect on economic performance. Our work has two implications: Firstly, collecting data on social networks remains challenging due to endogeneity. Secondly, network-enhancing policies should aim at improving both the internal connectivity of economic actors at the local level and their external connectivity with the rest of the world.     

Financing the sustainable management of Rwanda's protected areas

Rwanda's Nyungwe National Park is a biodiversity hotspot with the most endemic species in the ecoregion and the highest number of threatened species internationally. Nyungwe supplies critical ecosystem services to the Rwandan population including water provisioning and tourism services. Tourism in the Park has strong potential for financing enhanced visitor experiences and the sustainable management of the Park. This paper explores quantitatively the economic impacts of adjustment in Park visitation fees and tourism demand as a source of revenues to improve Park tourism opportunities and ongoing operations and maintenance. The methods developed in this paper are novel in integrating the results of stated preference techniques with a regional computable general equilibrium modelling approach to capture multisectoral, direct, indirect and induced impacts. Such methods have strong potential for assessing revenue generation alternatives in other contexts where park managers are faced with the need to generate additional revenue for sustainable park management while facing diminishing budget allocations. Results of this analysis demonstrate that adjustment of Park fees has a relatively small impact on the regional economy and well-being when compared with a strategy aimed at generating increased tourism demand through investment in improving the visitor experience at Nyungwe National Park.     

An example of multiple minima in a Cochrane-Orcutt procedure with multiple autocorrelation

We provide an example, based on an equation of the Canadian-US exchange rate, of multiple minima in a generalized Cochrane-Orcutt procedure. Our experiments suggest the need for search procedures in order to correctly identify autocorrelation structures.     

Limit theorems for reflected Ornstein–Uhlenbeck processes

This paper studies one‐dimensional Ornstein–Uhlenbeck (OU) processes, with the distinguishing feature that they are reflected on a single boundary (put at level 0) or two boundaries (put at levels 0 and d > 0). In the literature, they are referred to as reflected OU (ROU) and doubly reflected OU (DROU), respectively. For both cases, we explicitly determine the decay rates of the (transient) probability to reach a given extreme level. The methodology relies on sample‐path large deviations, so that we also identify the associated most likely paths. For DROU, we also consider the ‘idleness process’ L_t and the ‘loss process’ U_t, which are the minimal non‐decreasing processes, which make the OU process remain ≥ 0 and ≤ d, respectively. We derive central limit theorems (CLTs) for U_t and L_t, using techniques from stochastic integration and the martingale CLT.     

Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model

We extend the class of dynamic factor yield curve models in order to include macroeconomic factors. Our work benefits from recent developments in the dynamic factor literature related to the extraction of the common factors from a large panel of macroeconomic series and the estimation of the parameters in the model. We include these factors in a dynamic factor model for the yield curve, in which we model the salient structure of the yield curve by imposing smoothness restrictions on the yield factor loadings via cubic spline functions. We carry out a likelihood-based analysis in which we jointly consider a factor model for the yield curve, a factor model for the macroeconomic series, and their dynamic interactions with the latent dynamic factors. We illustrate the methodology by forecasting the U.S. term structure of interest rates. For this empirical study, we use a monthly time series panel of unsmoothed Fama–Bliss zero yields for treasuries of different maturities between 1970 and 2009, which we combine with a macro panel of 110 series over the same sample period. We show that the relationship between the macroeconomic factors and the yield curve data has an intuitive interpretation, and that there is interdependence between the yield and macroeconomic factors. Finally, we perform an extensive out-of-sample forecasting study. Our main conclusion is that macroeconomic variables can lead to more accurate yield curve forecasts.