Accounting for Confounders. We begin by ruling out omitted factors correlated with ∆diversity and conflict. Specifically, we follow a standard approach in heterogeneous DiD specifications and augment equation (3.4) with interactions of post-split and an array of confounding variables plausibly correlated with diversity and conflict. Our approach is twofold. First, we separately consider groups of initial predetermined variables chosen based on intuition and prior work (see, e.g., Fearon and Laitin, 2003; Esteban et al., 2012). These include, among others: security presence; public goods access; remoteness, trans- portation infrastructure and access to markets; population size and age distributions; nat- ural resource intensity; educational and occupational distributions; and topography, soil quality, and water access. Many are indeed highly correlated with diversity. 39 As shown in Appendix Tables C.8–C.11, some of these factors also mediate the effects of redistrict- ing on conflict. However, the key coefficients of interest on ∆P and ∆F remain mostly unchanged across these different specifications. There are of course hundreds of poten- tial confounding variables that one could combine in various ways in this type of exercise, and with limited degrees of freedom, this leaves the door open to cherry-picking (Gelman and Loken, 2014).
While mounting evidence documents the impact of neighborhood violence on children’s performance on standardized tests, less is known about the underlying mechanisms driving this effect. One leading hypothesis is that exposure to violence increases absenteeism, forc- ing kids to miss critical instruction and reducing their performance on subsequent stan- dardized tests. There is, however, little evidence documenting a causal link between neigh- borhood violence and absenteeism due in part to a dearth of appropriate data. In this paper we exploit daily absenteeism data for NYC public school children, combined with detailed, blockface-level crime data, to estimate the impact of exposure to neighborhood violence on absenteeism. Our results provide credible causal estimates of the impact of neighborhood violence on absenteeism, contributing both to the ongoing debate about how neighborhoods affect kids’ outcomes and to the growing literature on the causes of school absenteeism.
Based on the legislative history, I restrict the analysis to births occurred in years 1982 to 1986. This reflect a period when the Medicaid expansions focused primarily on the categorical eligibility rules. Specifically, the pre-policy period includes years 1982 to 1984. I use January 1985 as the first month of post-policy period, as this coincide with the state legislature convene timing of calendar year 1985 for most of the states. I end the post-policy period by December 1986 for two reasons. First, starting in April 1987, a subsequent policy change - the Omnibus Budget Reconciliation Act of 1986 (OBRA86) – was effective. The OBRA86 permitted states to increase income threshold for pregnant women to up to 100% of the poverty line. Variation occurred across states in adopting the expansion. On the other hand, the timing and generosity of state level expansions are potentially correlated with other state level unobserved attributes. To avoid state level legislative endogeneity concern, I exclude from the analysis sample births occurred after OBRA86 became effective. Second, I further exclude birth occurred in the first three month of 1987, to ensure that both pre-policy and post-policy sample are evenly distributed over the months of the year. Buckles and Hungerman (2013) documents substantial seasonality pattern of maternal characteristics.
This table lists summary statistics of the innovation factor, Fama-French three factors (from Kenneth French’s website), and Carhart momentum factor (constructed according to Carhart (1997). The five factors are denoted by RDCA (innovation factor), M KT (market factor), SM L (size factor), HM L (value factor), and M OM (momentum factor), respectively. In June of each year t, NYSE, Amex, and NASDAQ stocks are divided into three size groups using the breakpoints for the bottom 30%(Low), middle 40%(Medium), and top 30%(High) of the ranked values of market equity (price times shares outstanding from CRSP) in June for NYSE stocks. In each June, I also independently break NYSE, Amex, and NASDAQ stocks into three book-to-market groups based on the breakpoints for the bottom 30%, middle 40%, and top 30% of the ranked values of book-to-market ratio for NYSE stocks. Book-to-market ratio is calculated as the book value of equity in year t − 1 divided by the market value of equity in December of year t − 1. Aslo independently, in each June, I sort NYSE, Amex, and NASDAQ stocks into three innovation groups based on the breakpoints for the bottom 30%, middle 40%, and top 30% of the ranked value of RDCA, which is defined as R&D capital scale by total assets. 27 portfolios are formed from the intersections of the three size groups, three book-to-market groups, and three innovation groups. Monthly value-weighted returns on the 27 portfolios are calculated from July of year t to June of year t + 1, and the portfolios are rebalanced in June of each year. Thus, every month there are nine low R&D portfolios and nine high R&D portfolios. The innovation factor is defined as the difference, each month, between the simple average of the returns on the nine high R&D portfolios and the simple average of the returns on the nine low R&D portfolios. Panel A lists some basic statistics of the five factors. SKEW and KU RT refer to skewness and kurtosis, respectively. Panel B lists the correlation matrix of these factors. Panel C reports the coefficients of the regressions of innovation factor on traditional factors using two different asset pricing models: Fama-French three-factor model, and Carhart (1997) four-factor model. The sample period is from July 1963 to December 2009.
The manufacturing sector in India suffers from several issues when it comes to its access to elec- tricity. First, electricity prices for industrial consumers are higher than the marginal cost of supply. On the contrary, agricultural consumers and households are responsible for around half of electricity consumption but benefit from a reduced price. Thanks to these cross-subsidies from the industry, farmers pay only 12% of the average cost of power supply 12 , while households pay only 54%. Sec- ond, the Indian power grid suffers from systemic shortages as described in Allcott et al. (2016). These authors show that electricity shortages are one of the determinants of the rapid growth of self-generation by Indian industrials. Reasons for these shortages are multiple. Electricity prices never differentiate between peak and low demand periods. Hence, users do not adjust their con- sumption during peak time, which worsens existing electricity waste caused by the absence of proper consumption metering and low prices for non-industrials users. Allcott et al. (2016) note that there is no correlation between shortages and the median electricity price paid by manufacturing indus- tries, once state and year fixed effects are controlled for. It demonstrates that prices do not adjust to supply and demand in India, largely because the State Electricity Boards do not regularly up- date electricity tariffs. Power utilities lack the financial capacity to increase production even though their financial losses are covered by government subsidies. Given the importance of the necessary investment to expand and increase the reliability and capacity of public electric supply in India, the situation of the Indian power grid is only expected to improve slowly. Only 51.5% of the capacity
This dissertation consists of three independent essays in labor and publiceconomics. Chapter 1, the main chapter, presents evidence on the substitutability between workers within a fi rm, and between incumbent workers and outsid- ers, which matter for understanding the operation of internal labor markets and the consequences of worker turnover. To assess the substitutability of workers, I estimate how exogenous worker exits affect a fi rm’s demand for incumbent workers and new hires. Using matched employer-employee data based on the universe of German social security records, I analyze the effects of 34,000 unexpected worker deaths and show that these worker exits on average raise the remain- ing workers’ wages and retention probabilities for a period of several years. These fi ndings are diffi cult to reconcile with frictionless labor markets and perfect substitutability between incumbent workers and outsiders. The average effect masks substantial heterogeneity: coworkers in the same occupation as the deceased see positive wage effects; coworkers in other occupations instead experience wage decreases when a high-skilled worker or manager dies. Thus, coworkers in the same occupation appear to be substitutes, while high-skilled workers and managers appear to be complements to coworkers in other occupations. Finally, when the external labor market in the deceased’s occupation is thin, incumbents’ wages respond more and external hiring responds less to a worker death. The results suggest that thin external markets for skills lead to higher fi rm-specifi city of human capital and lower replaceability of incumbents.
Notes: This table presents the impact of air pollution on housing prices from years 2009 to 2014 for the sample of purchased properties that are located within 1 mile of at least one monitor. Observations within 2 months after and before the pollution spike (Dec 2010) are also excluded. All regressions are based on equation (2.1). The dependent variable is log of real price per-square meter. For each observation, the pollution index is the daily reading of nitrogen dioxide concentration from a monitor that the housing observation lies within the one mile of the given monitor. If a housing observation is close to more than one monitor, the pollution index is the average of readings from all close monitors. For columns (1) and (2), the Pollution Index is average of those daily pollution indices for one week before the time of each transaction. For columns (3) and (4), the Pollution Index is average of those daily pollution indices for one month before the time of each transaction. For columns (5) and (6), the Pollution Index is average of those daily pollution indices for three months before the time of each transaction. All specifications include 5-digit zip-code, year, and seasonal fixed effects. The even-numbered columns also include region trend fixed effects. Standard errors in all columns are clustered by 5-digit zip-code and stars indicate statistical significance level. * = 10 percent level, ** = 5 percent level. *** = 1 percent level.
Table 2.1 shows tax rates under old SDLT, new SDLT and LBTT. Fig- ure 2.1 shows total tax liability under each tax regime. The three schedules are numbered in the chronological order of their applicability in Scotland. The combination of these reforms creates interesting variation in tax liability in Scotland over time, which I will exploit for the empirical analysis that follows. I combine data from two sources. For the pre-LBTT period (i.e. before April 2015), I use administrative data on tax returns provided by HMRC cover- ing all property transactions in the UK. This dataset contains rich information on tax return for each transaction, but has very little information otherwise. For the post-LBTT period, I use total number of monthly transactions in £5000 bins provided by Revenue Scotland.
Jurisdictions that publicize school-level results typically update this information annually, raising concerns that parents may respond to year-to-year fluctuations that are largely noise (Kane and Staiger 2002, Mizala, Romaguera and Urquiola 2007). Our results show that English-speaking parents in low-income neighborhoods respond immediately to the first release of information, and continue to respond to subsequent releases in later years. Our data provide no way to determine whether these ongoing responses are a series of reactions to noisy information updates, or whether they simply reflect the time it takes for information to reach all members of the community. Likewise, the delayed response of non-English-speaking parents suggests substantial heterogeneity in parents’ access to public information. Consequently, annual releases of school achievement information that elicit ongoing media coverage may play an important role in communicating that information to all segments of the community, including recent immigrants.
The unit o f analysis and the unemployment measure seem more important in the models that add Medicaid eligibility and the unemployment*Medicaid interaction on the right hand side (lower panels o f Tables 2, 4, and 5). This is an appealing finding since the benefits o f using county-level data should be the largest in models which already have a state-level variable - Medicaid eligibility - on the right hand side. It is noteworthy, however, that the differences in results across the three model specifications are again not large. In particular, among black women, the interacted results do not reach statistical significance in any o f the model specifications but the coefficients mostly have the same sign. Among white women, unemployment per se decreases prenatal care use and the Medicaid ‘safety net’ increases it across all three specifications. Not surprisingly, the results are most significant when county-level cells are used (lower panels of Tables 2 and 4). In fact, the Medicaid ‘safety net’ is associated with significant benefits to infant and maternal health only when county-level cells are used (lower panels of Tables 2 and 4) and the results are most consistent across outcomes studied when county-level unemployment is also employed (lower panel of Tables 2).
The attentional mechanism is also supported by numerous studies. In an event-based design, Eisensee and Str¨omberg (2007) study the effects of competition between newsworthy events for public attention. Using two empirical designs, they show that disasters receive less aid from the United States when they face greater competition for television airtime. Gentzkow (2006) argues that the introduction of television, “crowded out” consumption of local radio and newspapers, which in turn decreased turnout in local elections. The nationwide marketing of the New York Times may have had similar effects (George and Waldfogel 2006). Olkean (2009) reports that improved television access decreased social capital and community activities in Javan villages. These effects may be viewed as manifestations of limited attention. Research in finance documents similar effects. Even highly incentivized and experienced investors have limited attention. Market behavior is sensitive to the timing of important announcements made at publicly known times (Dellavigna and Pollet 2009; Hirshleifer et al. 2009). Shifting the attention of investors appears to be one of the important roles of media coverage in financial markets (Barber and Odean 2008). Huberman and Regev (2001) document a stark case in which a news article drew attention to previously published cancer research and thereby generated enormous effects in biotech trading. Unlike the present experiment, these studies do not consider whether positive and negative news might have different effects on attention.
Even with the small negative wage impact of immigration, the distributional impacts on vari- ous kind of workers and capital owners may be larger and will depend on the skill mix of immigrant inflow in the labour force of host country, the changes in the composition of demand, sectoral and location choices of immigrants and change in non-wage income (Longhi et al. 2008). These factors will change over time. Furthermore, economic and broader impacts in the host country such as eco- nomic integration and demographic imbalances can be potential causes of concern as well. Focusing on these economic and labour market impacts of immigration in the host country, the public policy should be designed accordingly to respond to labour market needs and demographic objectives of the host country. The objective should be to manage the volume, origin, direction and composition of immigration inflows. One of the main results of the meta-analysis of the previous sections show that the impact of immigration on wages is smaller in more flexible economies as compared to those which more institutional rigidity. So reformation of labour markets policies to be less rigid may be help to increase immigrant economic integration by larger internal mobility of immigrants.
Yet, a growing number of studies in various fields, such as Economics, Psychology and Medicine, point in the opposite direction and suggest that decision makers assign a value to information that goes beyond the instrumental role considered by traditional economic theories. Every day life offers many instances of such anomalous attitudes towards information: we avoid information when we fear to receive bad news and we look for information when we expect good news or we want to confirm our opinions. This is especially true in health contexts, in which emotions such as anxiety and fear play an important role in driving decisions about medical treatments and preventive behavior in general. Consider for instance a patient who neglects medical tests when she has some clues of being ill, while she performs more accurate tests when she is almost certain of being healthy. In line with this, Lerman et al. (1998) show that 46% of subjects with an hereditary history of breast and ovarian cancer who perform a blood test to check for genetic mutations associated to these illnesses refuse to receive test results. Likewise, but with a social interaction component, Zanella and Banerjee (2014) find in a U.S. workplace environment that if a co-worker is diagnosed with breast cancer, the probability of subjects to perform a mammography decreases. 2
The previous difference-in-differences results show that, on average, there exists a relative increase in prices for houses sold in locations scheduled for redistricting. To gauge the magnitude of this redistricting plan on aggregate house values and tax revenue, I use property assessment data in 2013, one year before the start of redistricting process, to calculate the total gain in property values. I focus on houses that will be redistricted to the new school catchment area and multiply the 2013 value by the corresponding coefficient I find in the bottom line in Table 4.6. The results are listed in Table 4.7. The total increase in the housing stock value in Bryan Station is more than 85 million dollars from around 8,000 houses that will be redistricted into the proposed area. Henry Clay also has substantial increase around 15 million dollars. Though Lafayette has the largest estimate (10.4%) from previous section, but due to lower average house value and fewer houses, the total gain is less than the other two catchment areas. But the aggregate impact of the new school is large. The total value of housing stock in the three catchment areas amounts to more than 2 billion dollars and change of value is around 108 million dollars, an increase, on average, of $9016 per house. If I annualize the benefits over a 15 year period at a discount rate of 3.5%, this is a benefit of $783 per year per household. The estimated construction cost of the new high school was 82 million dollars 11 though this cost does not include any additional costs associated with maintenance of new facilities or any other costs not strictly a function of enrollments. As discussed in Section (4.3), to the extent that adding the new high school (Frederick Douglass) affects educational quality in the other high schools, the change in value is a measure of the relative benefits of the new school, not the absolute benefits.
I want to thank all the people who have supported and helped me while writing this disser- tation. In particular, I am indebted to my supervisor C. Katharina Spieß who "adopted" me as an external PhD student among her doctoral candidates at the Education and Family De- partment at DIW Berlin. I very much appreciate the extra work she put into guiding me through this dissertation over the years. Her valuable feedback and sometimes critical comments have considerably improved my work. Most importantly, however, I always felt that she believed in me completing this dissertation and gave much-needed encouragement. I am also grateful to everyone else at the Education and Family Department that I had the chance to work with, discuss with, and in general spend time with. The somewhat coin- cidental decision two or three years into this project to regularly work at DIW Berlin (I wanted direct access to SOEP regional data instead of SOEP remote) instead of my home environment proved to be one of the best strategic course-settings. The informal learning that took place on these occasions was invaluable to me. Apart from this, I always enjoyed the atmosphere at the department. I felt welcome at our monthly doctoral colloquiums from day one. In particular, I would like to thank Maximilian Bach, my co-author of Chapter 4, as well as Felix Weinhardt, Frauke Peter, Jan Marcus, and Jan Bietenbeck (although not a DIW employee) who have read parts of this dissertation and provided valuable feedback. Jan Marcus gets another thank you for agreeing to be my second supervisor.
While our argument will be much stronger if we can support our hypothesis with a consistent and continuous data set of visible and invisible trade costs, such data set is rare. 3 Alternatively, we turn to case studies with OECD’s aid for trade dataset to see whether the efforts to boost bilateral trade are strengthened when debt rene- gotiation happens. For the purpose of the paper, we restrict our attention to the categories of aid which are directly related to trade policy adjustment (See Table 7 for details). Figure 3.A.1 plots the change in aid (only for trade policy purposes) around the default period for the following three cases: Honduras in 2004, Congo in 2008 and Burundi in 2009. In the years of sovereign defaults, creditors double or triple their expense in trade-related aid to help defaulters out. They are generous with trade benefit instead of strict with harsh trade punishment. The case studies serve as indirect evidence for our hypothesis that creditors lower their trade costs with debtors.
The London School of Economics and Political Science Three Essays on Macro Labour Economics Jiajia Gu A thesis submitted to the Department of Economics of the London School of Economics for the degree[.]
Another related study is Rosero and Oosterbeek (2011), which evaluates the effect of home visits and child care centers on mothers and children in Ecuador. Child care centers provide day care for the whole day throughout the entire year, and groups of 8-10 children are supervised by a trained teacher. Weekly home visits, each lasting about an hour, teach mothers how to stimulate and nourish their children, in individual sessions if children are younger than three, and in groups if children are older. Rosero and Oosterbeek (2011) find that child care centers increase mothers’ labor force participation but have detrimental effects on children’s cognitive and health outcomes, while they observe the opposite effects for home visits. The early childhood development program that we study is more similar to the home visits than to the child centers described above. 3 However, while Rosero and Oosterbeek (2011) can analyze short term treatment effects only 4 , we are able to explore long term effects on the mother and children. Attanasio et al. (2014) also evaluate the effects of a weekly home visit program in Colombia that targeted children 12-24 months and lasted for 18 months. They find that enhancing mothers’ engagement with their children positively affects their cognitive and socio-emotional domains through an increase in parental investments and find no effects on mothers’ depression (Attanasio et al., 2014, 2015).
Departing from the assumption that each investor maximizes with regard to their local currency returns, it is possible that foreign investors especially in emerging markets maximize with regard to a basket of reserve currencies. Following this logic, Hypothesis 4 states that using FX correlation with regard to reserve currencies sees a stronger e↵ect than when using a general currency basket. I am using the definition of the IMF’s special drawing rights (SDR) valid from January 2006 to December 2010 as basket of reserve currencies. For the whole sample, SDR are pegged to US dollar, euro, British pound, and Japanese yen. 11 For consistency, I am using the same weights throughout the period fixed at 44%, 34%, 11%, and 11%, respectively. Columns (4)-(5) in Table 4.9 show the results. Similar to the previous regressions, the coefficient for FX correlation is significantly negative for the whole sample and the sub-sample of developed markets but insignificant for emerging markets. In line with Hypothesis 4, the coefficients in all three samples are more negative compared to Columns (1)-(3), however the di↵erence is not significant. Similarly, the explanatory power of the regressions using the reserve
A recent branch of the literature studies how natural disasters affect individual economic behaviors and outcomes. Caruso and Miller (2015), using data from the Peruvian census, study the effect of the 1970 Ancash earthquake on individual human capital accumulation, 37 years after the shock. They show that individuals affected by the earthquake while in utero are less educated, fare far worse in the marriage market and become parents at younger age. They also show that natural disasters have negative effects in the long-run and provide evidence of intergenerational transmission of shocks. Gignoux and Menéndez (2016) analyze the long-term effects of earthquakes on individual economic outcomes. Using survey data from rural Indonesia, they find that, following an earthquake, individuals experience short term losses but recover in the medium run (i.e. 2-5 years), and show income and welfare gains in the long run (i.e. 6-12 years). The positive long run effect is due to external aid, which enables to reconstruct the stocks of productive assets (mainly farms), to improve public infrastructures and to recover productivity.