Welfare services such as healthcare and education are commonly recognised as determinants of physical quality of life indices during the early phases of development in the third world. In order to benefit from these services, it is important that the general public have the mobility means to access welfare provision centres. However, very low vehicle ownership under the conditions of low per-capita incomes and large shares of population living in deep rural areas prevent the masses from accessing such services, thereby retarding the process of social development, which is reflected in the very poor physical quality of life indices in low-income countries.Public transportation could offer a viable and affordable solution to this apparent ambivalence. It could permit mobility for poor masses in spite of low per-capita vehicle ownership enabled by the national income levels. The present research demonstrates this strategic niche through an econometric examination of the evolution of the physical quality of life indices such as maternal mortality, infant mortality and literacy as against the healthcare, education and affordable mobility proxies in post-independent Sri Lanka. The country, which was then referred to as Ceylon, is often cited as a rare example of achieving social inclusion and reduced marginalisation and thereby a high social welfare standing, in spite of relatively poor per-capita income levels.

Recreation managers and planners recognize the importance of individual preferences and analysts have responded by incorporating individual and group-level heterogeneity in models of recreation behavior. We present a site choice model of recreational fishing that incorporates unobserved heterogeneity through a scale effect. By testing for scale heterogeneity, the model more accurately measures variation in site preferences compared with a conditional logit model, and demonstrates that site quality can affect fishing behavior unevenly across individuals. This result has important implications when using the model to predict fishing behavior and to value site quality and site access. We used the results to simulate the welfare impacts of several hypothetical improvements in fish abundance and find that ignoring scale heterogeneity can lead to inflated economic benefit estimates. Management implications-The information in this study can be used by fisheries managers to economically substantiate and motivate actions to enhance the benefits of recreational fishing. The analysis demonstrates that diversity of preferences means some anglers choose fishing sites based on information about catch and accessibility, while

The role of unobserved site attributes is a growing concern in recreation demand modeling. One solution in random utility models (RUM) involves separating estimation into two stages, where the RUM model is estimated with alternative-specific constants (ASCs) in the first stage, and the estimated ASCs are regressed on the observed site attributes in the second stage. Prior work estimates the second stage with OLS and 2SLS regression. We present an application with censored regression in the second stage. We show OLS produces inconsistent parameters when there are unvisited sites with no estimable ASCs and that censored regression avoids this problem.

An expectation to double the per capita income in five years through a sustained GDP growth rate of 9 per cent could only hold ground under very favourable economic conditions. On the one hand, this projected acceleration of economic activity, if practically realized, would demand a substantial amount of investment expenditure which could cause a widening of resource gap leading the economy into a debt trap. On the other hand, if the service sector including the transport sector could not augment to meet up the investments and expected output expansions, the targeted growth itself could be at risk. Neither scenario would be favourable. A way out of this apparent impasse is to increase investment productivity—by way of being observant in capital spending and improving the trickle-down effect of investment expenditure against mere capital accumulation.

The rapid growth of income inequality in the United States has unfolded unevenly across the country. Levels of, and changes in, income inequality within local economies have been spatially and temporally heterogeneous. While previous research has identified the correlates of subnational inequality, it has given less attention to the contribution of compositional changes. Drawing on commuting zone (CZ)-level estimates produced from U.S. Census and American Community Survey data, we extend the literature on subnational income inequality by addressing four main objectives. First, we track changes in the prevalence of five sets of inequality risk factors. Second, we measure the associations between these factors and within-CZ income inequality in 1980 and 2019 and describe changes in these relationships over time. Third, we decompose changes in within-CZ income inequality (1980-2019) into components attributable to changes in the prevalence of risk factors (i.e., composition effects) and changes in the penalties (i.e., coefficient effects) associated with each factor. Fourth, we compare the South to other regions in these respects to explore relevant patterns of socioeconomic change unique to the South. We find substantively large shifts in the prevalence of all five sets of risk factors and significant changes in the penalties associated with many factors, especially the age and industrial structures of CZs. Shifts in penalties explained the largest overall share of changing inequality between 1980 and 2019, but these overall effects mask considerable heterogeneity in the strength and direction of changing penalties We also find significant regional variation in the size of coefficient effects and the relative contributions of composition and coefficient effects. Together, these analyses underscore the importance of simultaneously accounting for the prevalence of and penalties to inequality risk factors.