A new polymorph of N-(prop-2-yn­yl)tricyclo­[3.3.1.13,7]decane-1-carbox­amide

The alkynyl bond of the title compound, C14H19NO, has a length of 1.170 (5) Å. The amide function shows a trans conformation with respect to the carbonyl group characterized by the torsion angle O—C—N—H of −176 (2)°. There is an inter­molecular N—H⋯O hydrogen bond between the amide function and the carbonyl group. In addition, weak inter­molecular hydrogen bonds stabilize the crystal structure. A comparison with a polymorphic structure shows conformational differences with regard to the orientation of the carbonyl groups with respect to the adamantyl group [O—C—C—C = 96.2 (3)° in the title compound and 123.7 (2)° in the polymorph] and the orientations of the propargyl groups in relation to the carbonyl groups [O—C—C—C = −87.7 (3) and −58.7 (2)°, respectively]

Trends and Determinants of Rural Poverty: A Logistic Regression Analysis of Selected Districts of Punjab

Poverty is widespread in the rural areas, where the people are in a state of human deprivation with regard to incomes, clothing, housing, health care, education, sanitary facilities and human rights. Nearly 61 percent of the country’s populations live in rural areas. In Pakistan poverty has been increased in rural areas and is higher than urban areas. Of the total rural population 65 percent are directly or indirectly linked with agriculture sector. In Pakistan more than 44.8 percent people generate their income from agriculture sector, and the higher rate of increase in poverty in the rural areas has provoked debate on growth and productivity trends in the agriculture sector. Therefore, it is the need of the hour to determine such factors which affect the poverty status of a rural household. Utilising unique IFPRI (International Food Policy Research Institute) panel data together with sub-sample of PRHS (Pakistan Rural Household Survey) for two districts of Punjab (Attock and Faisalabad) the present study aim at analysing and estimating the rural poverty trends and determinants of rural poverty from the late 1980s to 2002. The data was analysed by using binary logistic model and head count measure. The results show that the chance of a household tripping to poverty increased due to increase in household size, dependency ratio, while, education, value of livestock, remittances and farming decreased the likelihood of being a poor. Moreover, the socio-economic opportunities as represented by the availability of infrastructure in the residential region also play a significant role in the level of poverty faced by a household. This study makes a modest contribution by attempting to analyse the need for focusing on anti-poverty policies, which can nip the evil in the bud.Rural Poverty, Poverty Trends, Agriculture Growth, Determinants

A note on the transitional behavior of the saving rate in the neo-classical growth model (the Cobb-Douglas case)

In this short note I clarify two features of Figure 2.3 in Barro and Sala-i-Martin (2004). The figure, as it appeared in the first and second editions of the book, is confusing if not wrong. I hope this note will serve as a corrigendum to the figure.Transition dynamics; Saving rate; Neo-classical growth model

Intangible Capital, Barriers to Technology Adoption and Cross-Country Income Differences

I add intangible capital to a variant of the neoclassical growth model and study the implications of this extension for cross-country income differences. I calibrate the parameters associated with intangible capital by using new estimates of investment in intangibles by Corrado et al. [2006]. I find that the addition of intangible capital significantly improves the model's ability to account for cross-country income differences. Specifically, when intangible capital is added to the model, the required TFP ratio to explain observed income differences falls from 4.05 to 2.97. I also study variants of the model with endogenous and exogenous barriers to accumulation of technology capital, which consists of intangible capital and a fraction of physical capital that embodies technology. The addition of endogenous barriers, for reasonable parameter values, has a very small positive effect on the ability of the model to account for income differences. The addition of exogenous barriers suggests that huge cross-country differences in such barriers are needed to generate the observed income differences.Cross-country Income Differences; Intangible Capital; Technology Adoption

Intangible Capital and International Income Differences

I add intangible capital to a variant of the neoclassical growth model and study the implications for cross-country income differences. I calibrate the parameters associated with intangible capital by using new estimates of investment in intangibles by Corrado et al. (2006). When intangible capital is added to the model, the TFP elasticity of output increases from 2.14 to 2.64. This finding implies that the addition of intangible capital increases the ability of the neoclassical growth model to explain international income differences by more than a factor of two.International Income Differences; Intangible Capital