UCLA

This dissertation consists of three essays divided into chapters. In chapter 1, I analyze the identification of a simultaneous binary response model without nonadditive unobservable random terms, and suggest an estimation method. In particular, the derivatives of structural equations are identified and estimated. The identification relies on a special regressor, which enters the underlying structural equation linearly. All other exogenous variables held constant, variation on this special regressor generates variation on the structural equation which determines the latent endogenous variable in a known way, so we can recover the conditional distribution of the structural equations. The estimator can be constructed using a least-squares method, after replacing the elements of a matrix with kernel density and density derivative estimates. The estimator is shown to be consistent and asymptotically normal.

In chapter 2, I examine the determinants smartphone adoption among the elderly in South Korea. The advent of smartphones has caused a dramatic change in access to information and media, leading to a super-connected world of real-time services. Meanwhile, the constant dissemination of new technologies makes the digital divide multi-layered. In particular, older persons fall far behind the overall population in the access and use of new devices. To understand the technological environment following the introduction of smartphones and other smart mobile devices, I examine individual, household, and regional factors that can influence the preferences of the elderly with regard to obtaining a smartphone. I find that smartphone ownership among the elderly is mainly determined by personal rather than family characteristics. Also, I find that the area where a person lives has a significant effect on the probability of their owning a smartphone.

In chapter 3, I analyze the evolution of preferences for brands in digital camera market. A consumer considers the value of a brand, as well as product characteristics when deciding which product to buy. One way to capture this effect is to use brand-specific dummy variables. However, including brand-specific dummy variables does not fully account for the variation of the unit sales of compact digital cameras, since the preference for digital camera brands evolves over time. Assuming that the brand preference is affected by the advertising expenditure of each brand and the reputation among consumers, I suggest a method to capture the time-varying brand preference under the specification of BLP model.