The Kyoto Protocol is an international agreement signed in 1997 to reduce emissions of carbon dioxide and mitigate the consequences of global climate change. Early studies of the effectiveness of the Kyoto Protocol have attributed it to approximately a 7%–10% reduction in global carbon dioxide emissions. Given the carbon intensity of cement manufacturing, we examine the impact of the Kyoto Protocol on cement manufacturing output and carbon dioxide emissions. We are especially concerned about whether the Kyoto Protocol may have led cement manufacturing to move to places without binding emissions targets, thus resulting in carbon leakage. We find that nations with binding emissions targets under the Kyoto Protocol saw a 5% reduction in both cement manufacturing and carbon dioxide emissions from cement manufacturing compared to other nations, suggesting that the Kyoto Protocol may have led to technological innovation in cement manufacturing. Using data on carbon intensities for cement manufacturing, we support this notion and find further evidence that it fostered diffusion of existing, cleaner technologies from relatively more developed nations during the first phase, and technical innovation by these nations during the second phase, resulting in significant reductions in carbon dioxide emissions.
Climate policy affects the economy. Economists typically consider the economic costs associated with climate policy, but not all economic consequences of climate policy are necessarily negative. This paper considers the impact of the Kyoto Protocol on the international trade network for timber products and the competition graph derived therefrom. Implementing an instrumental variables difference-in-differences approach which uses a panel of centrality and clustering measures describing the relative importance of individual nations in the international trade network for timber products, this paper finds that nations that set a binding emissions target under the Kyoto Protocol saw the centrality of their position within this network decrease. Since the nations which set binding emissions targets were also the wealthiest nations, an additional consequence is that less wealthy economies became relative more important members of this international trade network. This is likely due to nations with a binding emissions target placing an increased importance on forested land for carbon sequestration. These results are extended to the competition graph of the international trade network for timber products where it is found that nations with binding emissions targets became marginally less important. However, increased clustering among nations with binding emissions targets in the competition graph occurred as a consequence of the Kyoto Protocol. Collectively, these results indicate that the competitive playing field was leveled in the international timber trade network while helping make progress towards multiple economically and environmentally oriented United Nations Sustainable Development Goals.
Core-periphery models are a commonly used and powerful tool in network analysis which allow researchers to identify a set of highly influential members (the core) based on the structure of the network. However, there is no standard method for core identification. Worse yet, for researchers in fields such as economics, existing methods often do not allow for researchers to make meaningful inferences from core-periphery analyses. This paper introduces a new method using integer programming to identify the core of a weighted network with either symmetric or asymmetric relationships and without the aid of any a priori assumptions. The integer program maximizes the weighted influence of the members of the core while imposing a set of user-parameterized connectivity constraints, both within the core and between the core and the periphery. As a result, this model generalizes previous concepts of the core of a network, i.e., an idealized core, through the flexibility created by the two connectivity parameters. These parameters give researchers the freedom to apply discipline specific theory to core-periphery analyses. This approach also offers drastically improved handling of directed data compared to existing methods of core-periphery analysis. An algorithm which converts the initially non-linear integer program into a linear integer programming approach is presented, and several examples are studied using this method to demonstrate its efficacy including a data set of international collaborations in academic publications and a data set of US railway shipments.
The COVID-19 pandemic increased the risk of travelling, working, and participating in public events. To test whether there were gendered differences in the response to COVID-19, we examine the behavior of male and female professional tennis players. We use data from major tennis tournaments which included a rather large number of athletes withdrawing from play. After controlling for past performance, wealth, and other relevant player attributes, we find that female tennis players were more likely to withdraw. This suggests that high-earning women may have greater risk aversion, especially related to COVID-19, than their male counterparts. Importantly, women were more risk-averse when it comes to international travel.
Introduction: The use of telemedicine increased during the global Coronavirus disease 2019 (COVID-19) pandemic. Rural populations often struggle with adequate access to care while simultaneously experiencing multiple health disparities. Yet, telemedicine use during the COVID-19 pandemic has been understudied on its effect on visit completion in rural populations. The primary purpose of this study is to understand how telemedicine delivery of family medicine care affects patient access and visit completion rates in a rural primary care setting. Methods: We performed a retrospective cohort study on primary care patient visits at an academic family medicine clinic that serves a largely rural population. We gathered patient demographic and visit type and completion data on all patients seen in the West Virginia University Department of Family Medicine between January 2019 and November 2020. Results: The final sample included 110,999 patient visits, including 13,013 telemedicine visit types. Our results show that telemedicine can increase completion rates by about 20% among a sample of all ages and a sample of adults only. Working-aged persons are more likely to complete telemedicine visits. Older persons with higher risk scores are more likely to complete their visits if they use telemedicine. Conclusions: Telemedicine can be a tool to improve patient access to primary care in rural populations. Our findings suggest that telemedicine may facilitate access to care for difficult-to-reach patients, such as those in rural areas, as well as those who have rigid work schedules, live longer distances from the clinic, have complex health problems, and are from areas of higher poverty and/or lower education.
Recent research in cryptocurrencies has considered the effects of the behavior of individuals on the price of cryptocurrencies through actions such as social media usage. However, some celebrities have gone as far as affixing their celebrity to a specific cryptocurrency, becoming a crypto-tastemaker. One such example occurred in April 2021 when Elon Musk claimed via Twitter that ``SpaceX is going to put a literal Dogecoin on the literal moon". He later called himself the ``Dogefather" as he announced that he would be hosting Saturday Night Live (SNL) on May 8, 2021. By performing sentiment analysis on relevant tweets during the time he was hosting SNL, evidence is found that negative perceptions of Musk's performance led to a decline in the price of Dogecoin, which dropped 23.4% during the time Musk was on air. This shows that cryptocurrencies are affected in real time by the behaviors of crypto-tastemakers.
This paper is a replication and extension of Buitenzorgy and Mol (2011). We recreate the data and analyses from that paper on the impact of democracy on deforestation from 1990 through 2000 with great precision before extending the data set and analyses to include the period from 2000 through 2010. We find that the original results of Buitenzorgy and Mol (2011) were spurious and inconsistent in the replication once heteroskedasticity robust standard errors were employed. When combining the two time periods and running analyses on panel data and differenced data for robust outcomes and better policy inferences, we find different results for the effect of democracy on deforestation, indicating that model specification is critical to studying this relationship. The more econometrically sound method, the differenced models, reject the Environmental Kuznet's Curve (EKC) hypothesis for democracy and deforestation, instead indicating that democracy decreased deforestation rates. When adding democracy spillover effects to the model, i.e., the impact on deforestation rates due to changes in democracy levels in neighboring countries, we still find that democracy leads to decreased rates of deforestation. We also find that having more democratic neighbors leads to further decreases in democracy. These outcomes have far-reaching implications for the blocs examined, which are highlighted in this study.
Working Papers
How and Where the Kyoto Protocol Affected Forest Cover: Evidence from Satellite Data (with Piper Zimmerman)
The Clean Development Mechanisms of the Kyoto Protocol incentivize the (developed) nations that set binding emissions targets to invest in sustainable forest projects in developing nations. Since we know that the Kyoto Protocol was largely successful at reducing emissions, and also that several nations needed to exploit these Clean Development Mechanisms in order to meet their emissions targets, a reasonable question to ask is if the Kyoto Protocol had a measurable effect on forest cover, and if so, where? To answer this question, we use satellite forest cover data and an instrumental variables difference-in-differences approach to estimate the effect of setting a binding emissions target under the Kyoto Protocol on annual percentage changes in forest cover. Our combined results suggest that the Kyoto Protocol did have a positive effect on the annual percentage change in forest cover in the poorest of developing nations. Combined with previous literature, this suggests that the Kyoto Protocol promoted environmentally and economically sustainable growth in global forest cover.
Post-Kyoto Emissions in the United States
In this paper I show that even though the United States (US) did not ratify the Kyoto Protocol, it still largely behaved like a nation with a binding emissions target under the Kyoto Protocol. This is determined by running two sets of synthetic controls models - one using a sample comprised of nations that set a binding emissions target under the Kyoto Protocol, and one using a sample of nations that did not set a binding emissions target. With the exception of methane emissions, the emissions profile of the US resembles its counterparts who did set a binding emissions target. Thus, the US effectively reduced greenhouse emissions similarly to nations that set binding emissions targets under the Kyoto Protocol, but, by opting for natural gas, the US would not experience the same level of public health gains associated with reducing emissions. Given this, the the primary implication for future climate policy is that, on the margin, ratifying a binding emissions target is the better choice for the potential signatory as it leads to a more fully internalized externality.
Road Network Structure and Air Pollution: Moving Beyond the Fundamental Law of Road Congestion (with Heather Stephens)
Transportation is one of the primary contributors to local pollution stocks and flows. This paper considers how the structure of local road networks and the accompanying vehicular emissions might affect pollution stocks and flows. A pollution stock and flow model building on the Fundamental Law of Road Congestion that considers the impact of road network structure is presented and used to generate hypotheses for how the structure of road networks should affect pollution stocks and flows. The main avenues for these effects are via traffic congestion and the opportunity cost of driving. Using topological indices to describe the structure of road networks, these hypotheses are tested using a Hausman-Taylor approach using a measure of urban form as an instrument to address the endogeneity of the network structure. Evidence is found supporting the hypotheses that better connected road networks, i.e., those with fewer bottlenecks and which generally allow for more efficient traversal, lead to lower levels of pollution stocks and flows. Evidence is also found that drivers adapt to more circuitous road networks with lower levels of driving. These mechanisms are confirmed by regressing measures of congestion and the opportunity cost of driving against the topological indices.
Exit Discrimination Against Black Head Coaches in the National Football League (with Brad Humphreys)
Exit discrimination occurs when a firm fires an employee because of their race rather than their productivity. Motivated by the recent firing of Black NFL head coach Brian Flores, this paper develops evidence of exit discrimination in the market for NFL head coaches using a Cox proportional hazard model and a panel data set on coaching tenure and performance, focusing on anti-Black exit discrimination. We analyze data on the career performance NFL head coaches in the post-Super Bowl (1966-) era. We find evidence that black head coaches face exit discrimination in the NFL. Black head coaches were more than four times as likely to be fired as an equally productive white head coach over this period. As an unintended consequence of this analysis, we also find evidence that the Rooney Rule successfully eliminated a pre-existing bias towards hiring white coaches.
Time Zones, Productivity, and Discontinuities in the Spatial (Dis)Equilibrium
Time zones represent an unexplored discontinuity in spatial equilibrium models in the form of increased barriers to the amenities that come with agglomeration economies. In this paper I show that sorting along time zone boundaries is not in equilibrium, and that productivity gains are possible in counties on the ``wrong'' side of the boundary in certain cases. To accomplish this, I first exploit the change of Mercer County, North Dakota from Mountain Time to Central Time to show that there were gains in physical productivity among participants in the Bismarck Marathon and Half-Marathon using a difference-in-differences framework. I then build on this result by applying the same framework to industry-level job count data and find that changing time zones caused an increase in job creation in Mercer County. I then provide direct evidence of a spatial disequilibrium around time zone boundaries by estimating the effect of being on the ``good'' side of a time zone boundary on total migration inflows as well as net migration within metro areas in four metro areas near the boundary between Eastern Time and Central Time. I find that people prefer to move to the ``good'' side of the boundary in both scenarios. Collectively these results imply that counties on the ``bad'' side of a time zone boundary stand to make significant economic gains by moving to the ``good'' side of the time zone boundary, and that people are actively leaving counties on the ``bad'' side for counties on the ``good'' side. Finally, to motivate the idea that time zones affecting sleep is a mechanism for these effects, I develop a model of sleep and productivity with a time zone effect. Solving the model shows that workers on the ``bad'' side of the boundary get less sleep, are less productive, and, consequentially, pay less in rent. This model prediction is empirically verified by a regression using median rent data from the American Community Survey.
Air Pollution and Physical Productivity: Evidence From Ultramarathons (with Heather Stephens)
Air pollution is known to lower worker productivity in myriad settings. However, causal inference studies with reliable air pollution data studying the effect of air pollution on physical productivity in outdoor settings over periods of time comparable to a workday are sparse. Furthermore, identification of the specific pollutant(s) responsible for this effect is even less common. By using ultramarathon race performances as a measure of physical productivity and spatiotemporal variation in ambient pollution levels, it is determined that particulate matter (PM10) is the key pollutant responsible for decreasing consistent, metered physical productivity in outdoor settings, with a 1% increase in ambient levels of particulate matter leading to a 0.071% decrease in physical productivity as measured by ultramarathon race performance. In addition to this, this paper also extends the existing literature by suggesting a distinction in which pollutants affect physical productivity along an aerobic/anaerobic divide, thereby explaining part of the existing ozone-particulate matter divide in the air pollution and physical productivity literature, as well as by providing the first evidence of gender based differences in the effects of air pollution on physical productivity.
The Golden Ticket: Examining the Impact of Winning the Western States Endurance Run Lottery on Subsequent Ultramarathon Performance and Travel Decisions (with Evan Bennett)
The Western States Endurance Run (WSER) is the premier 100 mile trail race in the United States. Due to requirements put in place by the United States Forest Service, there are only a limited number of participants allowed to compete in any given year. These participants are selected through a lottery for which they must first qualify by running a qualifying performance at another event. For these reasons, the WSER is a “bucket list” event for many ultramarathon runners. We exploit the randomness of the lottery to determine if winning the WSER lottery affects the training and travel behavior of lottery winners. We find that WSER lottery winners compete in more races, perform better in these races, and travel more in the short run (1-2 years). However, in the long run, lottery winners compete in fewer events, travel less, and compete in smaller events than lottery losers. This confirms that WSER is a “bucket list” event and extends the literature on the behavior of lottery winners to the context of ultramarathons.