This dissertation emcompasses three empirical studies in environmental and development economics. In Chapter 1, I study whether electricity use in newer or older residential buildings rises more in response to high temperature in a region of Southern California. Peak electricity demand occurs at the highest temperatures which are predicted to increase due to climate change. Understanding how newer buildings differ from older buildings improves forecasts of how peak electricity use will grow over time. Newer buildings are subject to stricter building energy codes, but are larger and more likely to have air conditioning; hence, the cumulative effect is ambiguous. This paper combines four large datasets of building and household characteristics, weather data, and utility data to estimate the electricity-temperature response of different building vintages. Estimation results show that new buildings (1970-2000) have a statistically significantly higher temperature response (i.e., use more electricity) than old buildings (pre-1970). Auxiliary regressions with controls for number of bedrooms, income, square footage, central air conditioning, ownership, and type of residential structure partially decompose the effect. Though California has had extensive energy efficiency building standards that by themselves would lower temperature response for new buildings, the cumulative effect of new buildings is an increase in temperature response. As new buildings are added, aggregate temperature response is predicted to increase.

In Chapter 2, my co-authors and I investigate the effect of cap-and-trade regulation of CO2 on firm profits by performing an event study of a CO2 price crash in the EU market. We examine returns for 90 stocks from carbon intensive industries and 600 stocks in the broad EUROSTOXX index. Firms in carbon intensive, or electricity intensive industries, but not involved in international trade were most hurt by the event. This implies investors were focused on product price impacts, rather than compliance costs. We find evidence that firms' net allowance positions also strongly influenced the share price response to the decline in allowance prices.

In Chapter 3, my co-authors and I measure and examine data error in health, education and income statistics used to construct the Human Development Index. We identify three sources of data error which are due to (i) data updating, (ii) formula revisions and (iii) thresholds to classify a country's development status. We propose a simple statistical framework to calculate country specific measures of data uncertainty and investigate how data error biases rank assignments. We find that up to 34% of countries are misclassified and, by replicating prior studies, we show that key estimated parameters vary by up to 100% due to data error.