Aggregate consumption and commodity prices

In this dissertation, I investigate whether liquidity constraint models can provide the microfoundations for the time series of aggregate consumption.;The second chapter explores whether relaxing the assumption of infinite horizons can explain the excess smoothness of consumption puzzle. The results are similar to the infinite horizons model. Firstly, with complete information, aggregate consumption remains as volatile as aggregate wage income. Secondly, imperfect information reduces the volatility of aggregate consumption; nevertheless, the magnitude of predicted consumption volatility is not significantly lower than what is predicted by the infinite horizons model.;The third chapter examines the finite sample properties of three simulation based estimators in the context of the non-linear rational expectations speculative storage model for commodity prices. The three estimators considered are the Method of Simulated Moments (MSM), Indirect Inference (IND) and the Efficient Method of Moments (GT). MSM is straightforward to implement; nevertheless the choice of moments matters and there is no a priori way to determine which moments to match. IND has good finite sample properties but is computationally demanding with a non-linear auxiliary model. GT has good finite sample properties but the choice of auxiliary model matters; the auxiliary model must be chosen to capture as closely as possible the features of the data.;The first chapter is an infinite horizons liquidity constraints model, where individual earnings processes are consistent with previous microeconometric evidence and the aggregate components are chosen appropriately to fit aggregate per capita labor income for the United States. I make two distinct assumptions about the information structure in the economy. With complete information, individuals can decompose an earnings shock in its aggregate and idiosyncratic components, whereas incomplete information is defined as the inability to distinguish between aggregate and idiosyncratic earnings shocks. The complete information model yields the counterfactual prediction that aggregate consumption is as volatile as aggregate labor income. The incomplete information model performs better; predicted aggregate consumption is not as volatile as aggregate labor income. Nevertheless, observed aggregate consumption remains excessively smooth given the observed log random walk nature of aggregate earnings.