Essays on Applied Econometrics

Abstract

This dissertation consists of three essays. The first essay analyzes the determinants of Foreign Direct Investment (FDI) in the food products sector in Turkey. An Autoregressive Distributed Lag (ARDL) model which is originally proposed by Pesaran and Shin (1999) and popularized by Pesaran et al. (2001) is applied to the monthly data over the period of January, 2009, to December, 2016. In the model, FDI inflows are modeled as a function of degree of openness, exchange rate, export price, and wage rate. The empirical results confirm there is evidence of a long-run equilibrium relationship among these variables in Turkey. Findings indicate that degree of openness, and export price have a positive sign and are statistically significant, while the wage rate presents a negative sign and is statistically significant. Finally, the cumulative sum (CUSUM) and the cumulative sum of squares (CUSUMQ) stability tests are employed to check the stability of short-run and long-run coefficients in the ARDL error correction model, and the results confirm that the model is structurally stable. Essay 2 examines the relationship between the exchange rate and tourism trade balance in Turkey from year 1970 to 2016 by applying three Vector autoregression (VAR) models. The main findings of this paper can be documented as follows: (i) there is no long-run co-integration relationship among the variables (ii) the reaction of the export revenue to an unexpected 1% depreciation exchange rate shock is positive and statistically significant at the 95% level (iii) the import tourism spending exhibits a robust significant positive response to home demand shock (iv) the response of trade balance to 1% shock in exchange rate is negative and significant, which shows the evidence of J-curve behavior for the selected eight European countries The final essay uses household survey data to analyze the relationship between education and poverty in Turkey. To obtain robust estimates of the determinants of household poverty, we applied five different econometric techniques, each relying on a different set of assumptions. such as Ordinary Least Squares (OLS), Linear Probability Model (LPM), Probit and Logit Models, and Instrumental Variable (IV) Probit Model. Both Ordinary Least Squares (OLS) and Linear Probability Model (LPM) model show that the level of education, being female and married, having a job or being retired are the important factors in determining the household head’s poverty conditions. However, employing probit and logit models, the results from the analysis provide evidence that married head of households are significantly more likely to poor than single head of households. In addition, the probability of being poor decreases with the household head’s educational attainment. However, based on the findings from Instrumental Variable (IV) Probit model, the policy reform, which was implemented in 1961, only increases the household head’s years of education for rural residents. Further, the higher the level of education of the household head, the higher the household per capita income.