Forecasting electricity demand using generalized long memory

This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is compared with a SARIMA benchmark using the years of 1999 and 2000 as the out-of-sample. The model clearly outperforms the benchmark. We conclude for general long memory in the series.

The impact of the 2008 economic recession on three residential property type investments: a case study of five diverse zip codes in Washington DC, USA

There has been 47 recessions in the United States of America (US) since 1790. US recessions have increasingly affected economies of other countries in the world as nations become more and more interdependent on each other. The worst economic recession so far was the “Great Depression” – an economic recession that was caused by the 1929 crash of the stock market in the US. The 2008 economic recession in the US was a result of the burst of the “housing bubble” created by predatory lending. The economic recession resulted in increased unemployment (according to NBER 8.7 million jobs were lost from Feb. 2008 to Feb. 2010); decrease in GDP by 5.1%; increase in poverty level from 12.1% (2007) to 16.0% (2008) (NBER) This dissertation is an attempt to research the impact of the 2008 economic recession on different types of residential investments: a case study of five (5) diverse neighborhoods/zip codes in Washington DC, USA The main findings were that the effect of the 2008 economic depression on the different types of residential properties was dependent on the location of the property and the demographics/socio-economic factors associated with that location.

The not so generalized effects of nonreciprocal trade agreements

This dissertation uses an empirical gravity equation approach to study the relationship between nonreciprocal trade agreements (NRTAs) and members’ trade flows. Estimations relate bilateral imports to trade policy variables using a very comprehensive dataset with over fifty years of data. Results show that meager average trade effects exist only if members are excluded from the world trading system or if they are very poor. As trade flows between NRTA members are already rising before their creation, results also suggest a strong endogeneity concerning their formation. Moreover, estimations show that uncertainty and discretion tend to critically hinder NRTA’s performance. On the other hand, reciprocal trade agreements show the opposite pattern regardless of members’ income status.Encouraging developing countries’ openness to trade through reciprocal liberalization emerges consequently as a possible policy implication.