Public choice literature divides the rationality of voting between instrumental and expressive. In this paper, we take the Vermont legislature in passing the H. 57 bill as a case to explain some of the determinants of expressive voting empirically. The H.57 bill declares that no government entity can interfere with, or restrict, a consenting individual’s right to abortion care across the entire gestation period. However, the bill has not changed the previously status quo of the state towards abortion rights. Thus, it creates a situation in which we can analyze the legislator’s voting behavior through the lens of an expressive voting framework. We utilize a high dimensional dataset and post-double-selection LASSO method to explain the channels that influence the expressive voting on the H. 57 bill. We web scrape the lower and upper chamber voting data on H.57 bill and use the 2017 American Community Survey 5-year estimates to retrieve 89 different socioeconomic, housing, and demographic characteristics of State Legislative Districts. Our results suggest channels of poverty, gender, and population diversity are some crucial mechanisms.

We evaluate the relationship between various energy markets at different quantiles of their respective return distributions by employing the recently developed cross-quantilogram method and the quantile Granger causality test. Three important open questions in the energy literature are revisited, namely, the "decoupling" of crude oil and natural gas prices, the mixed relationship between natural gas and electricity prices, and the "rockets and feathers" effect between crude oil and petroleum product prices. We find positive and significant spillover effects from crude oil to natural gas during bearish market conditions, which have weakened after 2013, suggesting a possible delink between the two markets in recent years. We further find a bi-directional causality at different market conditions for natural gas and electricity returns, especially at moderate and high return quantiles. However, in recent years the two markets have become more correlated during periods with low returns due to the transition of the natural gas power plants from peak to baseload facilities. Finally, our results do not find evidence for the "rockets and feathers" effect from crude oil to either the gasoline or heating oil market as we do not observe more significant spillovers during bullish market conditions.

This paper analyzes the volatility patterns of oil and natural gas prices in the United States and how they have changed due to economic policy uncertainty in the pre- and post-shale era. Using Markov-Switching GARCH models, we find evidence of heterogeneous volatility regimes for both commodities (i.e., high vs. low volatility). While the volatility persistence for oil is similar during the two sub-periods, significant changes have occurred to the natural gas market. Using quantile regressions, we find that economic policy uncertainty increases the probability of agitated market conditions of both markets, although this effect has weakened during the post-shale period.

In 2012, Vermont became the first state in the US to ban hydraulic fracturing for natural gas and oil production despite having zero known natural gas reserves. We evaluate the role of legislator and median voter characteristics on Vermont General Assembly voting outcomes on Act 152, which essentially bans fracking in the state. Using a double-selection post-Least Absolute Shrinkage and Selection Operator approach, we find evidence that campaign donations and being a member of the Democratic Party are positively related to voting to ban fracking. Median voter characteristics appear not to play an essential role in shaping legislator voting behaviour, corroborating the theory of expressive voting on the decision to ban fracking in Vermont.

Endogeneity problems such as self-selection and program placement bias are key issues in estimating the impact of microcredit programs. Self-selection problem occurs when borrowers select themselves in the program because they might have entrepreneurial skills, and risk taking abilities. Hence they could do better even without the credit. And, program placement bias occurs when a branch of microfinance institution placed in a developed village in order to become financially sustainable. This study focuses on overcoming these two biases while estimating the role of microcredit in alleviating poverty in Bangladesh. This study empirically estimates Foster-Greer-Thorbecke (FGT) poverty measures which are: incidence of poverty, poverty gap and squared poverty gap. To achieve the objectives of the study, primary data were collected from 2,598 households during the period of June 2014 to September 2014. The survey covers 24 districts out of 64 districts in Bangladesh. In addition to current borrowers, four types of control groups, non-borrowers, drop-outs, refused and pipeline borrowers, were interviewed to control for potential self-selection bias. The results of the FGT poverty measures indicate that the incidence of poverty, poverty gap and squared poverty gap are the lowest among borrowers. Then, this study applies fixed-effect logistic regression for measuring the impact of microcredit on the incidence of poverty and fixed-effect Tobit regression for estimating the poverty gap and squared poverty gap. In the empirical estimations, this study controls for age and education of the head of households, female (spouse) education, and age and gender composition of the household members. The results suggest that microcredit borrowers are less likely to be poor after being involved in the program. The results also indicate that microcredit program reduces poverty gap and squared poverty gap by respectively 3.3 and 1.2 percent even after controlling for self-selection and program placement bias. Therefore, this study claims that microcredit is an effective tool for poverty reduction.

We analyze potential efficiency gains in wind power projects by comparing counterfactual investment decisions in two different scenarios under a real options framework. The first scenario is a standard wind power investment, where the investor rents the land from local farms. In the second scenario, the wind power investor buys the land and commercializes both electricity and crop production, thus reducing the revenue risk through the diversification. Both scenarios have a waiting option, with the wholesale prices leading the installation decision. We model the electricity price as a mean reverting process with jumps and with different jumping probabilities for the different seasons of the year. Corn prices follow a mean reverting process. The waiting flexibility was modeled as a bundle of European options. The results indicate that the waiting option is exercised in 100% of our simulations in both scenarios, suggesting the still important role of government policies to stimulate wind power. More importantly, in more than 90% of the simulations, the second scenario brought value to the investment. Furthermore, net present values are more sensitive to reductions in capital costs than electricity prices. These results can form the basis for more effective policies for the wind power sector.

The level of market integration is a critical indicator of resource allocation efficiency. In this paper, we evaluate the dynamic spatial integration in the U.S. natural gas market since deregulation and the relative importance of each location in the overall price discovery process. Using data from seven natural gas spot markets in the U.S, as well as one Canadian spot market located on the border between U.S. and Canada, we find that the U.S. regional natural gas market is on average well-integrated in both the short- and long-runs. The connectedness price index we constructed ranges between 55% and 85% during the sample period (1994–2016). Though the connectedness of the market has generally improved, a marked decline has occurred over the past few years, coincident with the shale gas boom. This decline may be attributed to pipeline capacity constraints in an increasingly oversupplied market and the relatively small number of market participants voluntarily reporting transaction activities to price indexes. We find that the role of each regional market in the overall price discovery process has undergone several shifts during our sample period, depending on the specific market conditions at both the national and regional level. Of the eight locations, Henry Hub and Oneok appear to be the two most active markets, both transmitting and receiving a substantial amount of information throughout most of the sample period.