Research Summary (original) (raw)

Estimating the Neutral Real Interest Rate for the Philippines (Bangko Sentral ng Pilipinas, 2017) The research estimated the Philippine neutral real interest rates using various econometric methods including yield curves, statistical filters, state space models, structural approaches, and multivariate regression. It also evaluated if monetary policies appeared to have responded appropriately to inflation pressures by determining the correlation between the real interest rate gap and the inflation gap. Market Herding in the Philippine Equities Market (Bangko Sentral ng Pilipinas, 2017) Using the Hwang and Salmon Model, the report estimated the extent of market herding in the Philippine equities market for the period 1990 to 2015. These estimates may be used to guide investment decisions, to inform financial stability policy discussions, and to supplement the Philippine Financial Stress Index (PFSI), the index currently used by the Bangko Sentral ng Pilipinas to evaluate the level of market stress in the Philippine economy. Impact of Monetary Policy on Lending Activities of Philippine Banks (Bangko Sentral ng Pilipinas, 2017) Building on Kashyap and Stein (2000) econometric specification for the bank lending channel in monetary policy transmission in the United States, the research determined the impact of monetary policies on lending activities of Philippine banks using a two-step regression which evaluated the correlation between the strength of banks' balance sheet, their lending activities, and monetary policy. Modeling Exchange Rate Dynamics: Exchange Rates as a Function of Fundamentals, Market Herding, and Central Bank Intervention (Dissertation, Fordham University, 2012) This dissertation proposed a model for forecasting spot exchange rates and exchange rate volatility. The model, which posited that exchange rate dynamics is determined by three groups of variables, namely, macroeconomic fundamentals, market herding, and the impact of reported or rumored central bank (CB) intervention, was tested using the USD-Euro exchange rate for the period January 1999 to December 2009. Results of the empirical tests show that the model performed well in forecasting daily spot rates and monthly FX volatilities. In daily spot rates, the model was slightly less efficient than random walk but more efficient than Dornbusch-Frankel. For the volatility forecast, the model was slightly more efficient than the market. A possible explanation for the model's performance might be found in Frankel (1991) who noted that participants could improve their volatility forecasts by putting more weight on the long-run average. By incorporating variables for macroeconomic fundamentals, market herding behavior, and impact of CB intervention, the model provided a method for estimating the weight that should be assigned for fundamentals as well as for the extrapolating or trend-chasing tendencies of the market. Russian Federation Export Diversification through Competition and Innovation: A Policy Agenda*