My dissertation research applies dynamic optimization and panel-data methods to study household welfare in the United States and broiler poultry farms in Nigeria. The first chapter examines if persistent poverty among subpopulations in the United States can be explained by a poverty trap. Using panel data spanning over 40 years (1969-2017), we employ the most current nonparametric, semiparametric, and parametric estimation methods to test for a poverty trap. Our results indicate that there is no multiple equilibrium poverty trap in the United States generally, nor among female and black headed households. We find a single stable equilibrium that varies by the race and gender of the household head but is always above the U.S Census poverty line. These results are consistent across estimation methods and time periods. However, we find strong evidence of conditional convergence across subpopulations in the United States. We consistently observe black-headed households converging to significantly lower equilibrium than white-headed households. We also find some evidence of a gap between female and male headed households. While conditional convergence for blacks is robust to the choice of method or time period, for female headed households the income gap is shrinking, consistent with improvements in the gender wage gap. Chapters 2 and 3 focus on optimal decisions of commercial poultry farms in Nigeria using a discrete time and space dynamic programming (DP) algorithm, disaggregated by firm size. In Chapter 2, we explore the profitability of commercial farms facing rising input costs and increasing energy needs due to the adoption of climate mitigating technologies. Using a cross-sectional dataset and a one-year weekly panel of farm inputs and prices, we employ a dynamic programming model to determine the source of economies of scale among commercial poultry farms. In the presence of high feed costs and increased energy needs, the optimal strategy for medium sized farms is to sell and exit the industry. However, it remains profitable for large firms to stay in the sector. The findings are robust to various alternative model assumptions and specifications. They indicate that broiler farms need larger flock sizes to withstand negative input price shocks and expand energy consumption in the face of volatile and hotter temperatures. The sensitivity of the poultry industry to changes in feed prices is a major threat to the growth and survival of farms and highlight the importance of developing risk management mechanisms to counteract the effects of unstable prices. Chapter 3 examines the effect of electricity supply fluctuations on poultry farmer storage and freezer investment decisions. We combine a replacement and storage model to derive optimal storage rules. Then, we use expected cash flows from the model to derive freezer investment rules under uncertainty, due to fluctuating electricity supply and stochastic broiler and diesel prices. We find evidence that poultry farmers would use the storage option to take advantage of arbitrage opportunities and price premiums, but poor electricity supply hinders this. Despite positive gains from storage, freezer investments are not an optimal strategy due to high freezer costs and the need for generator use to complement poor electricity supply. The findings of this research (and its implications) are applicable across developing countries in Africa and Latin America that face scarce electricity supply and are in the process of expanding commercialized agricultural value chains as a way to increase farm incomes and stimulate economic growth