Use of select mortality tables for forecasting the number of recipients of different types of Pensions

At present, planning of the number of pensioners during execution of the budget of the RF Pension Fund is carried out on the basis of analysis of the state statistical accounting data on the population number and mortality. Construction of mortality tables by categories of pensioners on the basis of summarizing the data available at the RF Pension Fund and further use thereof during planning of the budget will permit achieving both forecasting of the number of pensioners by means of moving of ages and planning of expenditures for payment of pensions and benefits as a whole with higher accuracy.     

A toolkit for macrostructural regional forecasting: Methodological approaches and results of computations

This paper discusses the issues of developing a consistent system of forecast computations providing a long-term outlook for the Russian economy in both sectoral and regional contexts. Under special focus is the formation of regional development scenarios. Such scenarios are suggested to be based on the territorial pattern of investments into the national economy. Results of computations are presented for the period up to 2030 for two scenarios.     

Relative Effects of IFRS Adoption and IFRS Convergence on Financial Statement Comparability

One of the primary objectives of both adoption of IFRS and convergence between IFRS and U.S. GAAP is to increase financial statement comparability. Using a unique setting in Germany, we compare the effectiveness of these two approaches in achieving this desired outcome. Our empirical tests show that both adoption and convergence lead to an increase in comparability after the new enforcement regulation in 2005. However, difference‐in‐differences tests show that adoption does not lead to a significant incremental increase in comparability beyond convergence. The findings of this study should be of interest to regulators and standard setters as they assess alternative methods of aligning domestic standards with IFRS.     

Growth Enhancement Support Scheme (GESS) and Farmers’ Fertilizer Use in Rural Nigeria

Fertilizer use in Nigeria is estimated at 13 kg/ha, which is far below the 200 kg/ha recommended by the Food and Agricultural Organization (FAO). The objective of this investigation was to identify the determinant factors of farmers’ participation in Nigeria's Growth Enhancement Support Scheme (GESS). In addition, we determined the impact of the GESS on fertilizer use in rural areas. A total of 1,200 rural farmers were sampled across the six geopolitical zones of Nigeria. Results from the use of a recursive bivariate probit model indicated that GESS significantly impacted on the access and usage of fertilizer among the rural farmers; and that contact with extension agents, ownership of mobile phones, power for charging phone batteries, value output, mobile network coverage, ability to read and write were positive determinants of rural farmers’ participation in the GESS; whereas increased distance to registration and collection centers, and cultural constraints to married women reduced farmers’ tendency to participate in the GESS. The findings suggest that farmers’ participation in the GESS is a critical factor for raising fertilizer use in Nigeria. This implies that food security in sub‐Saharan Africa can be achieved by increasing the participation of rural farmers in the GESS.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.