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There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

This paper examines the hypotheses that the length and the depth of the Great Depression were a result of sticky prices or sticky nominal wages using panel data for industrialized and semi-industrialized countries. The results show that price stickiness, particularly, and wage stickiness were key propagating factors during the first years of the Depression. It is found that prices adjusted slowly to wages, particularly in manufacturing. Manufacturing wages are also found to adjust relatively slowly to innovations in prices, but unemployment exerted strong downward pressure on wage growth.

The purpose of this study is to analyze structural changes that took place in the cotton industry and develop a statistical model that reflects the current drivers of U.S. upland cotton prices. This study concludes that a structural break in the U.S. cotton industry occurred in 1999, and that world cotton supply has become an important determinant of U.S. cotton prices. The model developed here forecasts changes in U.S. cotton price based on changes in U.S. cotton supply, changes in U.S. stocks-to-use ratio (S/U), changes in China's net imports as a share of world consumption, the proportion of U.S. cotton engaged in the loan program, and changes in world supply of cotton.

Within the framework of potential efforts and strategies to employment generation for young people in Africa in general and Ethiopia in particular, the agricultural sector is increasingly considered as an important sector and a valuable means for poverty reduction, the promotion of economic development, and youth's economic independence. Renewed hope is placed on the sector to offer sustainable livelihood prospects for the rural youth. Yet, the success and sustainability of the sector require a proper understanding of how households allocate youth labor time in the sector and whether agricultural labor supply is responsive to economic incentives such as shadow wages. Using gender- and age-specific plot-level panel data, we systematically analyze the impacts of shadow wages of each household member on youth agricultural labor supply across types of farms. The results indicate that agricultural shadow wages matter for the youth's labor supply in the sector, but the impact differs for male and female youth. We also show that trends and patterns of youth labor supply vary across gender and whether they work on their own farm, and so do their labor returns. The results are consistent after controlling for individual heterogeneity and instrumenting for possible endogeneity. Taking into account the intensity of youth's actual involvement in the family farm, own farm or off-farm work instead of their stated intentions, the results challenge the presumption that youth are abandoning agriculture, at least in agricultural potential areas of Ethiopia. Instead, the frequent narrative of youth disengaging from agriculture may be a result of methodological flaws or data limitations. The findings suggest that it is necessary to invest in agricultural development to enhance labor productivity and employability of young people in agriculture.

Using the 1995 Third Industrial Census data in China, I explore the impact of inward FDI on the productivity performance of domestic SOEs. Multilevel analyses of city- and firm-level data show that presence of FDI-related firms (sanzi qiye) in a city significantly improves the total factor productivity of SOEs that are located in the same city but not affiliated with FDI. I interpret the effects as not only technology spillovers but also as FDI-induced institutional innovations and reforms.

Indian higher education system is supposed to be the source of equal opportunities to all students irrespective of their life circumstances. Does it succeed in realizing this ideal? In fact, the system of higher education inadvertently plays a critical role in constructing and recreating the inequalities between groups. The prime victims of inequality are first-generation students, whose disadvantages are unseen, their voices ignored. In India, first-generation students are typically confronted with the dynamics of caste-based inequality in addition to their deficiency in cultural and social capital. In this context, the purpose of this study was to examine the difference between who goes and who stops for higher education across generational status. Field survey data of 930 senior secondary students was employed as the basis for analysis. Findings of this study highlight that the gap between realization and planning is more in first-generation students as compared to their counterparts. Results of logistic regression indicate location, category, family income, academic achievement, stream of education, and social and cultural capital are pertinent factors that influence educational attainment of first-generation students.

This paper seeks to connect changes in the structure of wages at the occupation level to measures of the task content of jobs. We first present a simple model where skills are used to produce tasks, and changes in task prices are the underlying source of change in occupational wages. Using Current Population Survey (CPS) wage data and task measures from the O*NET, we document large changes in both the within and between dimensions of occupational wages over time, and find that these changes are well explained by changes in task prices likely induced by technological change and offshoring.

This chapter reviews the specification and application of the Deaton and Muellbauer's (1980) almost ideal demand system (AIDS) and the Christensen et al. (1975) translog (TL) demand system. In so doing we examine various refinements to these models, including ways of incorporating demographic effects, methods by which curvature conditions can be imposed, and issues associated with incorporating structural change and seasonal effects. We also review methods for adjusting for autocorrelation in the models' residuals. A set of empirical examples for the AIDS and the log TL version of the translog based on historical meat price and consumption data for the United States are also presented.