+ 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.
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
Parents and physicians may also manipulate the birth timing due to financial incentives. For physicians, Gruber et al. (1999) find that higher reimbursement fee triggers more C-section deliveries, the C-section procedure is one of the main mechanism of changing the timing of birth. A similar result was found by Grant (2009), his finding indicates that the one percentage point increase in C-section rate from about one-quarter of the original rate is attributed to an additional $1000 reimbursement for C-section procedure. For parents, Dickert-Conlin and Chandra (1999) find the increased tax benefit rise the probability of having the child in the last week of December rather than the first week of next year. Gans and Leigh (2009) find that in 2004 over 1000 births were moved from June to July to get the $3000 baby bonus, which is eligible for children born on or after July 1 st, 2004 in Australian. This shifting constituting 6 percent of the babies who would have been born in June. They also find the drop in the birth of June was mainly due to fewer C-section and induction procedures in June. And of the rise in births of July, half were C-section births, three-tenths were non-induced vaginal births, and two-tenths were induced vaginal births. All of these studies suggest that parents and physicians manipulate the birth timing because of monetary incentive, personal preference, unique cultures and so on.
Nevertheless, import exposure may be correlated with unobserved factors influencing employment and workers’ nationality. Also, the increase in Chinese import exposure may have been anticipated by workers and firms, which could have changed their behaviour accordingly. To avoid possible bias, Autor et al. (2013) instrument Chinese import exposure in the US with Chinese import exposure in other high income countries. While imports from China should be positively correlated across high income countries, imports from other countries are unlikely to be correlated with employment in the US manufacturing sector. In this paper, the first stage of 2SLS is the same as in Autor et al. (2013). The exclusion restriction requires that changes in import exposure in other high income countries do not affect workers’ nationality in the US manufacturing sector. Indeed, given that import exposure is likely to be positively correlated across high income countries, an increase in import exposure in the US is unlikely to induce large shifts of migrants towards similarly affected countries. Moreover, migrants deciding to move to the US face large relocating costs in changing their destination to Europe, Japan or Australia, making such a change quite unlikely. 4 Direct Chinese migration flows to the US are also quite unlikely to influence the results, since Chinese migration flows to the US are relatively scarce and, if anything, should decrease with the increase in international trade between China and the US.
Table 1.3 reports regression estimates of the sensitivity of changes in monthly credit spreads (CS t ) to changes in interest rates (TB t ) for the January 1973 to December 2014 period for two regimes and four different cases, with t-statistics displayed in parentheses and with the “L” index representing up to three lags. The bootstrapped P-values are reported in brackets below the t-statistics. In regime I&III, shocks to interest rates and credit spreads are either average or significantly positive, while in regime II&III they are either average or significantly negative, as defined by their magnitude with respect to a one-sigma deviation from the mean. Case 1 is the base model where the residuals 𝛼 t t and + t 𝛽 t in the VAR system (CS t = (TB L +CS L + 𝛼 t t )/(1-αβ) and TB t = (CS L +TB L + t 𝛽 t )/(1- αβ)) are estimated without any extra variable(s). Case 2 is the model where the residuals in the VAR system (CS t = (TB L +CS L + D t + 𝛼 t t )/(1-αβ) and TB t =(CS L +TB L + D t + t 𝛽 t )/(1-αβ)) are estimated with a dummy variable D t set to 1 between January 1973 and August 1981 and set to zero between September 1981 and December 2014. Case 3 is the model where the residuals in the VAR system (CS t = (TB L +CS L + [TB t -K t ]+ 𝛼 t t )/(1-αβ)and TB t =(CS L +TB L + [TB t -K t ]+ t 𝛽 t ))/(1-αβ)) are estimated with a mean-reverting level K t of interest rates calculated as a 5-year moving average. Case 4 is the model where the residuals in the VAR system (CS t =(TB L +CS L + D t + [TB t -K t ]+ 𝛼 t t )/(1-αβ)and TB t =(CS L +TB L + D t + [TB t - K t ]+ t 𝛽 t )/(1-αβ)) are estimated with both a dummy D t and a mean-reverting level K t . Panel A reports the results for investment-grade bonds, while panel B reports the results for high-yield bonds.
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.
religious and charitable organizations. More than 80% of employment associated with the NAICS code 813 is accounted for by the two more narrowly defined NAICS codes: 8131 (“religious organizations”) and 8134 (“social and civic organizations”). Since information on the NAICS code 813 is available for a larger number of counties, we use it for the construction of our baseline proxy, but consider the two more disaggregated codes in the robustness checks. We construct four alternative measures of SocialCapital (all expressed in terms of natural logarithms): (i) employment by the organizations classified under the NAICS code 813 over the total employment in a given a county, (ii) employment by the organizations classified under the NAICS code 813 per capita, (iii) the number of establishments classified under the NAICS code 813 over the total number of estab- lishments in a given county, (iv) the number establishments classified under the NAICS code 813 per capita. We use the first measure as our baseline proxy for social capital and consider the other three measures in the robustness checks. The idea behind approximat- ing social capital with the associational density builds on the seminal work by Putnam et al. (1994), Putnam (1995, 2000), who shows that participation in associational activ- ities boosts interaction and cooperation between community members and promotes the norms of reciprocity and trust. The advantage of our measure compared to alternative proxies suggested in the literature (such as voluntary blood donations or voter turnouts) is that it exploits oﬃcial data from the US Census and is therefore characterized by a high degree of validity and consistency. It is additionally well-suited for the ensuing panel data analysis since this measure is available on an annual basis for the vast majority of US counties over the entire period of 1986-2014. In the cross-sectional analysis, we take the (log of the) associational employment density averaged over 2000-2010 as our measure of SocialCapital.
In the 1980 census, women who lived in Alaska in five years ago (prior residents) had more children across all birth years than recent migrants, suggesting that migrants since 1975 did not prefer larger families. In the 1990 census, the pattern is largely the same, with the exception of the 1948-1950 birth cohort where new migrants had slightly more children than prior residents (in all other years the difference was not statistically different from zero, or showed prior residents having more children). Women born between 1948 and 1950 would have been 32 to 34 years old when the first dividend payments were disbursed, and thus outside of the age groups that showed the largest effects from the PFD (see Figure 2.7). The similarity of the differences between new migrants and prior residents in the 1980 and 1990 censuses provides suggestive evidence that the post-1985 migrants did not have differentially higher preferences for children than prior waves of Alaskan migrants. Together with the 1984 survey, these results suggest that the effects of the PFD on fertility were not driven by differential migration.
Previous studies have done a good job distinguishing between the impacts of voluntary and involuntarily delisting on stock prices, risk, and liquidity. Liu and Stowe’s (2005) study is identified as the earliest study in the international delisting field 23 (You et al., 2008). For a sample of U.S. firms that voluntary delisted from Tokyo Stock Exchange (TSE), they find no significant changes in returns on the day of the delisting announcement or the actual delisting day. Another comprehensive study by Liu (2004), where he examines a sample of 158 foreign firms that have been involuntarily delisted from U.S. stock exchanges, finds a significant average price drop of 4.5% upon the delisting announcement. Liu, in both studies, employs an event study approach to evaluate changes in the abnormal returns around actual delisting and its announcement. Both studies do not evaluate changes in the risk and subsequent change in the cost-of-capital. Harris et al. (2008) examine a sample of 1,098 firms that have been involuntarily delisted from Nasdaq, over the three-month period between the delisting announcement date and the actual delisting date. They observe a significant decline in stock prices and a large increase in volatility. Finally, You et al. (2008) conduct a comprehensive study on the valuation effect around cross-listing and subsequently delisting from foreign stock exchanges. They report significant negative returns in the month of actual delisting; however, this loss is temporary. In their sample, changes in risk around delisting vary, but it increases for the majority of the sample. In summary, for involuntary delisting, studies observe significant drop in stock returns around delisting, however, studies report no changes in returns around delisting for voluntary
With regard to the context of the thesis, two of the three studies present evidence from Benin, a country that has been studied in comparatively lesser detail than many of its African neighbours, but provides an interesting case study in development. A small Francophone West African country of around 11 million inhabitants, Benin is bordered by Togo, Burkina Faso, Niger and Nigeria. Benin has seen rapid development since the fall of the communist regime in the late 1980’s. Its economy is dominated by the service and agricultural sectors, with cotton representing the largest export. The country is, today, ruled by a comparatively stable democracy by African standards, and has seen stable growth levels in recent years. Yet, Benin is still faced with many challenges: poverty remains high and the gains from development have not been evenly shared geographically. Chapter 3 of this thesis studies an example of such uneven development in depth; whilst national primary school enrolment rates have seen almost unparalleled improvements since 1990, many regions have not shared in this progress and still lag behind. Furthermore, national completion rates have fallen somewhat, reflecting some of the difficulties that accompany such rapid progress. The country has also experienced rapid population growth since 1990, with the population having more than doubled in just 20 years. This has meant that even stable high growth rates of over 5% in recent years have not been sufficient to reduce poverty levels; the most recently available data suggests that over one third of Benin’s citizens still live in poverty – the poverty headcount ratio in 2011 was 36.2% (WDI, 2016). Furthermore, life expectancy remains low and child mortality high, with around 100 deaths per 1000 births, as of 2015.
as it rarely changes, and when it does, laws tend to change as well. Our setting bypasses these standard challenges. The Dodd-Frank Act caused the SEC to transfer oversight of “mid-sized” in- vestment advisers ($25-100 million in assets under management) from the SEC to state regulators, except for advisers located in Wyoming and New York. 29 This decision was announced on July 21, 2011 and in effect by January 1, 2012. The impetus for the shift was exogenous to mid-size adviser behavior. The intention was to free up SEC resources so that it could increase oversight of hedge funds and private equity firms. The size threshold was chosen out of convenience, as it would reverse a component of the 1996 National Securities Market Investment Act (NSMIA). NS- MIA had assigned mid-size advisers to the SEC as part of a broader effort to unify state-securities regulations. Just over 38% of all existing SEC-registered firms were affected by this re-juridiction. Using a differences-in-differences design, we study how a shift from SEC to state-regulator oversight affects the probability of a customer complaint. Complaints are a good measure of ad- viser misbehavior and better than available alternatives. Complaints are publicly disclosed and observable for every professional in the industry. In addition, complaints are preference-adjusted; regardless of preferences, complaints reveal the perception of substandard adviser advice. The most obvious alternative, studying investment returns, is sparsely available, and would yield un- suitable comparisons across clients of different preferences. Studying regulatory sanctions may instead represent change in regulator behavior, not adviser behavior. We construct a survivorship- bias-free panel dataset at the representative-year level. We narrow the time period to the three years before and after the implementation of Dodd-Frank (2009-2014). We assemble this data using a variety of regulatory disclosures made by the SEC.
This essay examines topics in health economics. 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.
Writing a dissertation is a journey, a journey that requires inspiration, perseverance, and deep commitment. For me, this journey could not have been completed without guidance and help from a large group of people. I wish to express my deepest gratitude to all of those who helped to make this journey a wonderful experience in my life and helped me contribute to the scholarly literature in economics.
Our contribution to the literature is three-fold. The primary contribution is that we are the first to consider the effect of housing vouchers on criminal outcomes for adult recipients using a randomized lottery. 2 We join an extensive crime literature produced by MTO, which, with the exception of Ludwig and Kling (2007) who studied the contagion effects of neighborhood crime on both adults and juveniles, primarily focuses on outcomes for youth whose families received vouchers. While most of these studies have found that MTO caused positive or neutral effects for female youth, their findings for male youth have been surprisingly negative (Clampet- Lundquist, Edin, Kling, and Duncan, 2011; Kling, Ludwig, and Katz, 2005; Sciandra, Sanbonmatsu, Duncan, Gennetian, Katz, Kessler, Kling, and Ludwig, 2013; Zuberi, 2012). The only exception is Katz, Kling, and Liebman (2001), who shows that male youth have less behavior problems after moving through MTO. The effect of Section 8 voucher receipt on adult criminal outcomes is yet to be documented although Jacob,
The London School of Economics and Political Science Three Essays in Applied Economics Amar Shanghavi January 2015 A thesis submitted to the Department of Economics of the London School of Economics f[.]