There is a fast growing body of recent literature on interconnection of commoditymarkets or the role of financialization in markets co-movements. Saghaian (2010) presents empirical results using vector autoregression (VAR) and Granger causality supplemented by a directed graph theory modeling approach to identify the links and plausible contemporaneous causal structures between energy and commodities in the grain sector (wheat, soybean and corn). Although Saghaian (2010) finds strong correlation among oil and food prices with monthly data from 1996 to 2008, there is mixed evidence of a causal link from oil to the other three commodities. B¨ uy¨ uk¸sahin and Robe (2017) model dynamic correlations between equity market and commodity in grains and livestock sector, and find that world business cycle shocks have a substantial and long-lasting impact on the food markets co-movements with equity market, while changes in the intensity of financial speculation have a short-lived and not significant impact on cross-market return linkages using various specifications of structural vector autoregression (SVAR). Tang and Xiong (2012) find increasing correlation since 2004, but they model dynamics of correlations by rolling-window for all pairwise combinations of commodities one after another, which is inefficient as they do not explicitly take all information into account and not necessarily robust to the structural change in correlations. Adams and Gl¨ uck (2015) consider structural breaks in correlations but their sample only include eight commodities and also do not provide a joint estimation of dependence structure in futures returns. Most of these studies, however, only focus on specific commodities or just use low frequency data (monthly or weekly), and one may want to know if these empirical results are still robust if relative high frequency information of more futures markets is used.
Table 1.9 presents the estimates for / 7 , / 8 , / 9 , and / ; in equation (1.4). Based on the p-values for the t-test (row (f) in each panel), we are unable to reject the null hypothesis that there is no differential impact of G2 LBW (or IUGR) on male children born to the high SES group in all panels across all models. In contrast, we find some evidence that females born to the high SES groups are less affected by the intergenerational correlation in LBW (or IUGR). Out of 16 coefficients (row (c) in each panel), three coefficients in panel A and one coefficient in panel B and panel C are statistically significant at the 5% level (two of these five are significant at the 1% level). In panel A, except for SGA (5th percentile), females born to LBW (or IUGR) mothers in a county with a low unemployment rate are 2.26-2.50 percentage points less likely to be LBW (or IUGR). This difference represents a decrease of around 30% as compared to the base-line incidence of LBW (or IUGR) in females. The evidence from town-level income and parental education is weaker. However, we only find a significant differential impact on females born into towns with high average income in the model with 2SD < mean (in panel B) and those born in counties with high parental education in the model with FT LBW (in panel C). 31 We find no differential impact on males and females born in counties that experienced the most improvement in SES (in panel D). Thus, our results weakly support the findings in the literature: children born into favorable socioeconomic conditions suffer less as a result of poor maternal health (Currie and Moretti 2007; Bhalotra and Rawlings 2013). Moreover, our findings indicate
Public reporting for nursing homes has existed for almost two decades since it was first introduced in 1998. Nursing Home Compare (NHC), which is a web-based nursing home report card, was launched by CMS (then known as the Health Care Financing Administration) in October 1998. Initially, only a few facility-level structural characteristics and information on health inspections were reported. The nurse staffing measure was added after 2000. After experimenting in six pilot states for six months, CMS introduced the Nursing Home Quality Initiative (NHQI) nationally in November 2002. In this version of the report card, quality indicators were introduced in addition to the existing health inspection and staffing information. Most recently in December 2008, CMS launched a newly designed five-star quality rating system that translates detailed and fragmented measures into more simplified and summarized stars ranging from one to five stars, with a higher number of stars indicating better quality.
(1997)) tested the unbiasedness hypothesis on the basis of cointegration. One of necessary conditions for cointegration technique to be valid is the assumption that time series are random walks. However, the question of whether commodity prices are random walks or trend stationary has never been settled. Several studies in testing if commodity futures prices are trends or random walks provide controversial results. Larson (1960) found evidence to support that prices move randomly, which means price changes reflect new information and hence approximate a random variation. Stevenson and Bear (1970) concluded that corn and soybean futures prices move in a systematic, as opposed to a random manner. Several recent papers discuss the question at a general level. Blough (1992a, b), Cochrane (1991), and Sims (1989) argued that the question of whether a time series has a unit root is inherently unanswerable on the basis of a finite sample of observations.
This essay examines topics in healtheconomics. The first study uses data obtained from the Health and Retirement Study (HRS) and the Rand HRS files, to examine the relationship between access to retiree health insurance (RHI) and the decision to leave one’s career job. This paper does not restrict attention to individual’s who choose to take a full retirement, as recent data indicates that only 51.4% of individuals leave a career job and fully retire, while nearly 25% leave their career job, and pursue a partial retirement. In this paper a Cox Proportional Hazard Model with time varying covariates is utilized to estimate the probability that an individual disengages from their career job, given they have not yet done so. Results indicate that those with access to RHI are significantly more likely to leave their career employer in all time periods than identical individuals without RHI.
Our main variable of interest in measuring the quality is the standard height and weight from the U.K. growth chart 2 . Researchers predominantly tend to use intelligence related measures including educational attainment and IQ scores to indicate the quality of children (J. Angrist et al., 2010; J. D. Angrist & Evans, 1998; Black et al., 2005; Blake, 1981; Conley & Glauber, 2006; Goux & Maurin, 2005; Guo & VanWey, 1999; Hanushek, 1992; J. Lee, 2008; Li, Zhang, & Zhu, 2008; Qian, 2009; Rosenzweig & Schultz, 1987; Rosenzweig & Wolpin, 1980; Rosenzweig & Zhang, 2009; Taubman, 1986; Zajonc & Markus, 1975). Some use labor market, marriage, and fertility outcomes to measure the quality (J. Angrist et al., 2010). A few study the birth weight related measures (Liu, 2013; Rosenzweig & Zhang, 2009). Because intelligence related measures have been widely used, we are going to focus on a less explored area—children’s weight and height measurements. Moreover, past studies heavily focus on the effect of increases in the number of children from two to three or even more. In contrast, our paper focuses on the effect of an additional child on the first one.
Information on smoking behavior is from the Current Population Survey To- bacco Use Supplements (CPS-TUS) for years 1998 to 2003 and 2006 to 2007. 8 The Current Population Survey is a nationally representative, monthly house- hold survey of labor force participation. The monthly survey often includes sets of supplemental questions on particular topic such as health, schooling, fertility, and immigration. Periodically, respondents are asked a series of questions about smoking and other tobacco-related behaviors as part of the Tobacco Use Supple- ment, which is sponsored by the National Cancer Institute and the Centers for Disease Control. The CPS-TUS is a repeated cross section of individuals useful for describing smoking behavior of Americans over time. Individuals who have smoked at least 100 cigarettes in their entire life are identified as current or for- mer smokers and are asked a series of follow-up questions about smoking behavior. The smoking measures used in this paper are self and proxy reports of smoking at least some days and smoking every day.
In 2018, over 67 thousand Americans died from a drug overdose (Hedegaard et al., 2020). Although the substantial rise in drug-related mortalities over the past decade has been largely driven by illicit opioid use, the origins of this epidemic are rooted in opioid prescribing patterns that began in the 1990s and persisted throughout the 2000s. While pharmaceutical companies, physicians, and patients have received increased scrutiny in recent years over their respective roles in the ongoing crisis, the actions and behaviors of private health insurers have gone largely overlooked. These firms play an integral role in coordinating care between large segments of the U.S. population and health care providers; as a result, health insurers are uniquely positioned to monitor and observe patterns of opioid prescribing and use. Furthermore, despite recent efforts at the federal level to address the opioid epidemic, many public health advocates contend that the most impactful change will occur through communal ventures. Because of their influence in local health care markets, developing a better understanding of how private health insurers’ incentives interact with enrollee opioid use is of first order concern.
less than 25 percent of wheat yields in Germany are explained by cumulative rainfall. Thus, producers’ yields are more likely to be affected by an individual mix of weather phenomena instead of the amount of sunshine, rainfall, or temperature. Fourth, while relatively higher risk can lead to higher risk premiums on weather derivatives, which partially explains the low acceptance of those products (Mahul, 1999; Duncan and Myers, 2000), regional separation, i.e. personalised or highly segregated areas, can help to reduce the risk and thus risk premiums on weather derivatives. This decreases the cost and threshold for producers to use such insurance products. However, due to the geographical concentration of mineral resources in often remote areas, this might not be possible for mining. Compared to farming and energy production, the locations of metal ores are limited and often remote. Mining companies must accept the given weather conditions in metal ore-rich areas instead of choosing the mining site. Based on the yearly production output of 2014 (USGS, 2015), Australia, Brazil, Guinea, India, and China represent primary mining countries for aluminium ores, i.e. bauxite. Overall, prior research highlights several reasons why commodity producers may stay away from weather derivatives to hedge their exposure to adverse weather. Although these products can reduce the financial distress for producers, the net effect of weather anomalies on the supply remains unchanged. That is, if weather events negatively affect the production and reduce the output, the supply will be reduced. This leads to a new equilibrium price on the market that may be partially compensated by existing inventory. Thus, one should still be able to observe the effect of weather anomalies on both inventory and price of the underlying commodity, regardless of whether or not weather events are hedged.
variable 𝐷𝑟𝑜𝑢𝑔ℎ𝑡. During this one-month period, corn nearby futures price declined 7.89%. Since the drought also affected the live cattle market, the variable 𝐷𝑟𝑜𝑢𝑔ℎ𝑡 for live cattle equals 1 from December 19, 2012, when nearby futures’ price peaked at 134.40 cents/lb after the drought, to May 20, 2013 when the price bottomed at 118.00 cents/lb. A more sustained collapse in cattle prices occurred in 2015 causing concerns about the price discovery function of the live cattle futures market. This period overlaps the time of CME’s pit trading closure, which was announced in February 2015 and started officially in July 2015. Therefore, we create the dummy 𝐷2015 which equals 1 in the year of 2015, to capture the possible joint price decline and pit closure. The corn market remained relatively stable during 2015, providing a good opportunity for identifying changes related to the pit trading closure. Consistent with Gousgounis and Onur (2017), we create a dummy variable 𝑃𝑖𝑡 that equals 1 after February 4, 2015 when the closing of pit trading was announced for corn. 9 Commodity index funds have increased investments in commodity futures markets (Irwin and Sanders, 2012). These funds typically follow a predetermined schedule to roll their positions from the nearby to the next nearby contract. Considering the vast position changes involved in the rolling process, changes may occur in the discovery process. We include a dummy variable 𝐼𝑛𝑑𝑒𝑥𝑟𝑜𝑙𝑙 that equals 1 between the fifth and tenth business days of the month prior to expiration, which includes the roll periods of the two largest commodity indices: S&P Goldman Sachs and Dow Jones UBS commodity indices. 2.4.5 Regression Results
Second, a malpractice incidence can severely damage a physician’s reputation, and as Dra- nove et al. (2012) have shown, such reputational damages are associated with economically significant costs. Direct monetary costs arise relatively seldom from a malpractice claim, as most physicians are fully insured against malpractice risks (Danzon 2000, Zeiler et al. 2007). For this reason, physicians should care more about the probability of being sued than awards. One goal of liability for medical malpractice is to align the interests of physicians and other healthcare providers with those of patients: by punishing healthcare professionals for providing too little care, liability is supposed to reduce adverse health outcomes. However, as we know since at least from Kessler and McClellan (1996), liability can also induce physicians to provide too much care. This is referred to as defensive medicine, which, in the economics literature, is defined as care that physicians order to avoid lawsuits but for which cost ex- ceeds expected benefits. The empirical evidence suggests that physicians practice defensive medicine by increasing treatment intensity for heart attack patients (Kessler and McClellan 1996, Avraham and Schanzenbach 2015) and ordering more imaging services (Baicker et al. 2007). The evidence regarding the rates of Cesarean sections, whose excessive use is of- ten attributed to liability pressure, is less conclusive: while Dubay et al. (1999) and Shurtz (2013) find that physicians perform more Cesarean sections following an increase in liability pressure, Currie and MacLeod (2008) and Amaral-Garcia et al. (2015) find the opposite.
Other studies exploit the discontinuity of retirement status around the official retirement age set by governments. If this discontinuity of retirement is significant, and all factors but retirement are smooth around the official retirement, RDD (regression discontinuity design) may have the potential to identify the short-term causal effects of retirement on health. For example, Johnston and Lee (2009) uses a RDD based on the discontinuity at age 65 in the probability of retirement in England to estimate the impact of retirement on subjective and objective health. Their results indicate that retirement increases an individual’s sense of well-being and their mental health. In German pension system, 60 is the pension eligibility age for women, for unemployment and partial retirement, and for severely disabled people; age 65 is the standard pension age. Using a RDD and two pension ages as cutoffs, Eibich (2015) identifies the causal effects of retirement on health and the mechanisms behind the effects, and finds that retirement improves subjective health status and mental health, while reduces outpatient care utilization. Relieving from work- related stress, increased sleep duration, as well as frequent physical activities seem to be key mechanisms through which retirement affects health. However, since the retirement behavior is voluntary in developed counties relative to developing countries, sometimes the discontinuity of retirement status of developed countries is not sharp enough to apply RDD approach. In addition, there may have other significant changes around retirement age for elderly. For example, age 65 is also the Medicare eligibility cutoff in the U.S. This health insurance availability may confound, or cause impact of the retirement to be biased upward.
This thesis contains the results of the research on health and labor markets that I have done as a Ph.D. student at Lehigh University. Many professors in Economics departments have provided valuable comments, both directly and indirectly to my research, and I really appreciate their help. Especially, I would like to express my warmest gratitude to some of them. First, I would like to thank my advisor Dr. Mary E. Deily. Her patient guidance, enthusiastic encouragement and valuable critiques are necessary for me to proceed through the Ph.D. program and complete this thesis. Besides, it is not an easy task to review a thesis, but she continuously provide thoughtful, extensive, and detailed comments. She has been a strong and supportive advisor to me, and I owe her my heartfelt appreciation. Second, I would like to thank my third-year-paper advisor Dr. Thomas J. Hyclak for teaching me valuable lessons about writing a paper. When I worked with him on my third-year paper, he provided careful and instructive comments that helps to shape and guide the direction of the work. Also, he provided brilliant ideas that enlighten me a lot on the fourth chapter of this thesis. Third, I would like to thank Dr. Shin-Yi Chou. She taught HealthEconomics when I was a second-year graduate student, and I learned a lot on how to read papers and to do empirical research from that class. She also provided insightful ideas and useful advice when I am doing the third chapter. Her excellent and timely feedback make me work more efficiently.
Chapter 2 – the first of the main chapters – addresses possible causes of vacancies in the housing market (i.e., unoccupied houses), which is becoming a more and more profound challenge for rural areas in the era of continuing urban concentration. Abundant vacan- cies can be found in regions with very diverse characteristics and are perceived as highly problematic. My co-author, Lars Vandrei, and I provide a detailed overview of theoreti- cal and empirical studies on vacancies. We, first, summarize theoretical approaches, which may explain the mechanisms leading to vacancies under the assumptions of the standard market model, search and matching theory and behavioral economics. Con- cerning the latter, we propose a new framework to explain vacancies in the housing market in the context of prospect theory. Second, we formulate hypotheses from these theories regarding the causes and the extent of vacancies. Then, we evaluate the validity of these hypotheses by referring to the existing empirical literature while comparing the data, samples and methods employed in the various studies. The main findings of our literature review are (1) that there is considerable room to extend existing theoretical models and (2) that some hypotheses have either been investigated by the empirical lit- erature only to a limited degree or have not been investigated at all. We also suggest that (3) a social welfare analysis that takes the specific type of vacancy into account is highly relevant for housing policy decisions. This chapter is an amended version of a published paper (see Fritzsche, C. and L. Vandrei (2014), Keiner will sie haben – Theoretische Ur- sachen für Immobilienleerstand, Credit and Capital Markets – Kredit und Kapital 47(3): 465-483). I prepared the description of the search and matching models, formulated the respective hypotheses and evaluated their validity with the existing empirical literature (Sections 2.2 and 3 in Chapter 2). Lars Vandrei described vacancies under the standard market model and proposed a new framework in order to explain vacancies in the hous- ing market in the context of prospect theory (Sections 2.1 and 2.3 in Chapter 2). To- gether, we prepared the discussion section.
Nonetheless, our results in combination with the high exposure to inter- national competition of certain industries give evidence to the notion that unilateral climate and energy policies are therefore accompanied by a great deal of uncertainty and substantial risks. It is not by chance that the IEA rec- ommends Switzerland to align its energy policies with its major trade partners ( IEA , 2012 ): “[Switzerland should] pursue closer integration with European energy markets and closest possible alignment of its energy policies with those of the European Union”. If extensive climate and energy policies are adapted without international coordination, our result that reveals substantial changes in the input mix even in the short run hint at the possibility that reverse ef- fects that are clearly beyond the scope of our analysis may be triggered. For example, alterations of factor prices of relatively immobile factors like labor, a certain degree of deindustrialization or even negative spill-overs on the environ- ment. It remains to note that alternatives to multilateral commitment exist, e.g. supplementary measures such as border tax adjustments or tax exempts for energy intensive industries. 16 Both possibilities have inherent drawbacks.
(2015), which proposes an extension of their basic equilibrium model while taking into account the informational frictions and incorporating a futures market. The authors suggest a realistic setting to highlight the role of informational noise by futures market trading, which affects commodity demand and spot prices. They propose in the timeline of the extended model that the three main traders (producers-long future, suppliers-short futures, and financial traders-long/short futures) in futures markets build their positions at time t=0 and choose to revise and unwind their positions before delivery at time t=1. In our empirical framework, to align with those authors’ notations, the producers and suppliers are presented as hedgers, while the financial traders in this study are represented by four other types of investor (MM, SW, OR, and NR). Sockin and Xiong (2015) assume that the learning effect takes place with one-period time lag and under- line interactive phenomena between suppliers and producers such that producers observe the private signals about global productivity at time zero, yet commodity suppliers observe that signal at time t=1. The proposed trading structure leads to two rounds of information aggregation, the first in the futures markets with informational noise originating from the activity of financial traders, and the second round of trading in the spot market when the financial traders unwind their futures positions and commodity suppliers (hedgers) observe a supply shock. In this context, the interaction among major influential traders is established; thus we forestall highlighting the nature, direction, and type of interactions among all agents (e.g. hedgers and managed money traders).
As the number of abortion restrictions in a state increases, so too does the cost of obtaining an abortion. Some of the restrictions directly raise the financial cost of an abortion, while others increase costs indirectly. For example, Medicaid funding restrictions force already poor women to take on the added expense of the abortion, despite the fact that many other pregnancy-related costs are typically covered by Medicaid. Limits on health insurance coverage require women to pay out of pocket, although they may have coverage for other medical procedures. Mandated waiting periods can add to the burden indirectly by increasing the amount of time a woman needs to set aside for the procedure, potentially resulting in lost wages and higher travel costs if she needs to travel a long distance to her provider and miss additional days of work. Parental involvement laws increase the psychological cost for teens seeking an abortion (Sabia and Rees, 2013), and could add to the financial cost if the minor travels to another state in order to obtain an abortion without her parents’ consent. Policies such as mandated counseling also add to the psychological toll without adding directly to the financial expense. The resulting cost increases are likely to be more burdensome for poor women than for those who can more easily absorb the additional expenses or circumvent stringent rules in their own states by traveling to more permissive states.
+ τ m + ν ti(m) + ω tr(m) + mt (3.1) Where i(m) and r(m) are the industry and region of the m th market and τ , ν and ω are market, year-industry and year-region fixed effect. Estimation of (3.1) with a fixed effect estimator implies that β is identified from within market variation across time. Market fixed characteristics and time varying shocks at the industry and region level are differenced out, implying that causal interpretation of the fixed effect estimate of β from an equation like (3.1) relies on immigrant-native mix being uncorrelated with industry-region-year specific shocks. In table 3.8, I display market transitions from Understanding Society data. 11 From year to year, 7.6% of natives and 9.5% of immigrants change market, i.e. they change either industry, region or both. Among those that move markets, the vast majority, above 80%, only change industry. For both natives and immigrants around 4% of those that change industry or region change both at the same time. This suggest that labour has a higher mobility response to industry rather than region shocks. Nonetheless, the fact that some workers change region and industry simultaneously means that there can be endogenous responses to industry-region specific shocks. To deal with this source of endogeneity I use the shift-share instrument pioneered in the migration literature by Altonji and Card (1991) and Card (2001) and widely applied since then (for UK examples see Bell et al. 2013; Ottaviano, Peri, and Wright 2018). The rationality behind this instrument comes through the effect of networks, where workers that are already settled in the receiving market provide connections to newcomers shifting their moving costs.
There has been considerable interest in analyzing the consequences of compulsory military service on a wide array of outcomes. These include earnings (Angrist, 1990; Angrist & Krueger, 1994; Angrist & Chen, 2011), education (Card & Lemieux, 2001), crime (Galiani et al., 2011; Lindo & Stoecker, 2014) and health outcomes (Bedard & Deschenes, 2006; Conley & Heerwig, 2012). This is in part due to the general policy interest in understanding shocks that are expected to have large and persistent long run effects on outcomes. Indeed, conscripted individuals are obliged to serve in a crucial time of their lives, usually characterized by critical human capital investments. Moreover, the mechanics underlying these early adulthood shocks are themselves of considerable interest. For example, the military service and disruption caused by conscription may directly have long run effects on labor market outcomes. Alternatively, conscription may instead affect long run outcomes through its effect on educational attainment, since continuing one’s education can typically allow one to defer mandatory military service. Finally, understanding the effects of compulsory military service has direct policy implications for countries that still have such policies in place. 1
In terms of the value-added to the literature, our primary contribution is to showcase the importance of looking at the worker-to-employer social preference angle. Our finding is interesting because it raises the possibility that positive social preference toward blacks, rarely detected in traditional labor markets, may emerge in environments such as the online platform economy where associative distaste is naturally muted. (Of course, long distance racial animus, or a desire to see an out-group person suffer losses, may still prevail.) Bear in mind, ours is a well-powered, AEA pre-registered experiment which would have detected preference-based discrimination had it existed on the M-Turk platform; the fact we don’t is encouraging, seeing how the online economy is expanding (Katz & Krueger, 2019). Further, it is oft-repeated that the relative lack of success of black-owned businesses or the diminished presence of blacks in leadership positions in the United States is a major concern among policy makers; more so, because “business ownership has historically been a route of economic advancement for disadvantaged groups” (Fairlie & Robb, 2007). Do entrepreneurial blacks shy away from business because they rationally fear discrimination by majority white workers? Our study does not document such fears on the part of black employers but offers some reason to question those fears in online-platform economies if they exist. Curiously, our finding also shuts down another line of thinking connected to the issue of anticipation of discrimination. There is some evidence that establish that the employer-to-employee discrimination is taste-based (see, for example, (Charles & Guryan, 2008)). What if it is being miss-classified? What if an employer discriminates against his out-race workers because he rationally believes/anticipates being discriminated against by them? In that case, the employer- to-employee discrimination ought to be characterized as statistical. Within the confines of our environment, our finding that workers do not discriminate against their out-race employers essentially shuts down any rational expectation of bias an employer may have. Incorrect beliefs may persist, though (Bohren, Haggag, Imas, & Pope, 2019).