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Inference and testing in general point process models such as the Hawkes model is predominantly based on asymptotic approximations for likelihoodbased estimators and tests, as originally developed in Ogata (1978). As an alternative, and to improve finite sample performance, this paper considers bootstrap-based inference for interval estimation and testing. Specifically, for a wide class of point process models we consider a novel bootstrap scheme labeled 'fixed intensity bootstrap' (FIB), where the conditional intensity is kept fixed across bootstrap repetitions. The FIB, which is very simple to implement and fast in practice, naturally extends previous ideas from the bootstrap literature on time series in discrete time, where the so-called 'fixed design' and 'fixed volatility' bootstrap schemes have shown to be particularly useful and effective. We compare the FIB with the classic recursive bootstrap, which is here labeled 'recursive intensity bootstrap' (RIB). In RIB algorithms, the intensity is stochastic in the bootstrap world and implementation of the bootstrap is more involved, due to its sequential structure. For both bootstrap schemes, no asymptotic theory is available; we therefore provide here a new bootstrap (asymptotic) theory, which allows to assess bootstrap validity. We also introduce novel 'nonparametric' FIB and RIB schemes, which are based on resampling time-changed transformations of the original waiting times. We show effectiveness of the different bootstrap schemes in finite samples through a set of detailed Monte Carlo experiments. As far as we are aware, this is the first detailed Monte Carlo study of bootstrap implementations for Hawkes-type processes. Finally, in order to illustrate, we provide applications of the bootstrap to both financial data and social media data.

This paper investigates the effects of automation and offshoring on the dynamics of the occupational distribution of employment with a focus on Western Europe between 2000 and 2016. I use a general equilibrium model with three regions, three types of workers, ICT capital, trade in final goods and endogenous offshoring. Fed with exogenous measures of ICT-capital prices and trade costs, the model replicates key features of the data. It matches the observed dynamics of offshoring to Eastern Europe and Asian countries. It also reproduces accurately the observed polarization of the labor market: abstract and manual labor increase while routine labor falls. A counterfactual experiment reveals that automation is the main driver of polarization. Since it is also the only factor that drives individuals to become abstract (highskill) workers, it is welfare enhancing. The effects of falling trade costs on labor polarization are smaller, but imply welfare gains.

This chapter focuses on the inner rationale and consequences of four different archetypal positions regarding how ethical and political values are tackled in welfare economics. Welfare economics is standardly associated with the welfarist framework, for which social welfare is based on individual utility only. Beyond this, we distinguish the value-neutrality claim – for which ethical values should be and are out of the scope of welfare economics –, the value confinement ideal – for which ethical values are acceptable if they are minimal and consensual–, the transparency requirement – for which any ethical values may be acceptable in the welfare economics framework if explicit and formalized –, and the entanglement claim – which challenges the very possibility of demarcation between facts and values.

Retirement system sustainability is defined as the ability of plan boards and managers to be responsible investors, active stewards, and allocators of capital to economic activities with desirable social and environmental outcomes. In this paper, we examine the policy frameworks and important structural variables pertinent to private retirement systems in Australia, the UK, and the US. By analyzing various reports, interviewing experts, and using data from the Principles of Responsible Investment as well as national pension and retirement authorities, we identify key structural challenges within national retirement systems. These include market fragmentation, principal-agent conflicts in personal pensions, and the role of service providers. Our results provide insight into how, or whether, retirement systems can facilitate desirable economic, social, and environmental outcomes.

I study criminal street gangs using new data that describes the geospatial distribution of gang territory in Chicago and its evolution over a 15-year period. Using an event study design, I show that city blocks entered by gangs experience sharp increases in the number of reported batteries (6%), narcotics violations (18.5%), weapons violations (9.8%), incidents of prostitution (51.9%), and criminal trespassing (19.6%). I also find a sharp reduction in the number of reported robberies (-8%). The findings cannot be explained by pre-existing trends in crime, changes in police surveillance, crime displacement, exposure to public housing demolitions, reporting effects, or demographic trends. Taken together, the evidence suggests that gangs cause small increases in violence in highly localized areas as a result of conflict over illegal markets. I also find evidence that gangs cause reductions in median property values (-$8,436.9) and household income (-$1,866.8). Motivated by these findings, I explore the relationship between the industrial organization of the black market and the supply of criminal activity. I find that gangs that are more internally fractured or operate in more competitive environments tend to generate more crime. This finding is inconsistent with simple, market-based models of criminal behavior, suggesting an important role for behavioral factors and social interactions in the production of gang violence.

Official foreign direct investment (FDI) statistics track FDI via direct investing nation rather than ultimate investing country (UIC). If a FDI project is sourced through an overseas subsidiary, normal FDI metrics will register that investment as being from the third country, not the home country of the multinational. There is a growing awareness that the large amount of FDI channeled through special purpose vehicles and offshore financial centers therefore makes official statistics unreliable: investment from certain nations may be significantly under or over counted. According to official statistics, the United States ranks 11th in terms of total amount of foreign direct investment (FDI) in Vietnam. As Vietnam joins the ranks of lower middle-income countries, and becomes more integrated into global value chains, a more representative methodology for calculating FDI would help Vietnam thoughtfully engage with foreign investors and support Vietnam's development objectives. This report, commissioned by the United States Agency for International Development (USAID) in Hanoi includes: 1) A literature review of FDI databases and FDI tracking methods, 2) a comparative analysis of the existing methods for tracking FDI via UIC, 3) a discussion on the feasibility of implementing those methods for Vietnam, 4) a novel method for estimating Vietnam’s inward FDI via UIC, 6) recommendations to USAID for further research and analysis.

Between 1909 and 1922 a private deposit insurance company coexisted with the state-sponsored deposit insurance program in Kansas. This paper documents its development using primary sources. In addition, it examines if affiliation with the private deposit insurance (i) had an effect on risk-taking and the probability of failure; (ii) increased confidence among depositors, and (iii) was influenced by a neighboring bank’s membership in the state’s deposit insurance. We find that affiliation with the private deposit insurance did not affect a bank’s likelihood of failure, although smaller national bank members did increase risk-taking. The evidence does not support the hypothesis that the company enhanced depositor confidence. Lastly, we do find strong evidence that a bank’s decision to join the private deposit insurance was influenced by neighboring banks’ affiliation with the Kansas deposit insurance program.

We study the reaction of investors to tail events across trading institutions. We conduct experiments in which investors bid on a financial asset that delivers a small positive reward in more than 99% of the cases and a large loss otherwise. The baseline treatment uses a repeated BDM mechanism whereas the market treatment replaces the uniform draw of the BDM mechanism by a uniform draw over the bids of the other participants. Our design is such that bids should not differ across treatments in normal times while allowing for potential differences to emerge after tail events have occurred. We find that markets tend to exacerbate the reaction of investors to tail losses and we attribute this effect to emotions.

This paper studies the spillover effect of home mortgage delinquencies using a discrete-choice spatial network model. In our empirical study, a main challenge in estimating this model is that mortgage repayment decisions can only be observed for a sample of all the borrowers in the study region. We show that the nested pseudolikelihood (NPL) algorithm can be readily modified to accommodate this missing data issue. Monte Carlo simulations indicate that the proposed estimator works well in finite samples and ignoring this issue leads to a downward bias in the estimated spillover effect. We estimate the model using data on single-family residential mortgage delinquencies in Clark County of Nevada in 2010, and find strong evidence of spillover effects. We also conduct some counterfactual experiments to illustrate the policy relevance of the spillover effect.

Technology can help to reduce inefficiencies and inequalities in developing countries. Although whether this happens in practice often depends on the social and geographic context. Deployment of solar home systems (SHS) across Nepal provides one such example. We examine a policy to promote SHS through a subsidy for adoption and its downstream benefits - children’s education, time allocated to agricultural and household work (both unpaid), and working for a wage. We overcome the challenges of the non-random assignment of subsidies by using geographic regression discontinuity design using (cost) distance as the assignment variable. This is based on the assumption that households cannot perfectly control the assignment variable because migrating to a different region, simply to acquire an additional solar subsidy of maximum NRs4000, is challenging and unlikely in the case of Nepal. Our results show that subsidy-eligible households are about 43% more likely to adopt SHS. We find a positive effect of the SHS adoption on the grade for age and educational z-score of children’s educations with the effect being higher on girls than boys. We also find that females are 14.2% more likely to participate and spend more time (about 19 extra days in a year) in agricultural practices by reducing their engagement in family work. However, there is no effect on the participation rates across the labour market. Results also show that males increase their contribution to household work.

This paper provides invariance theorems that facilitate testing for the existence of an asset price bubble in a market where the price evolves as a Markov diffusion process. The test involves only the properties of the price process’ quadratic variation under the statistical probability. It does not require an estimate of either the equivalent local martingale measure or the asset’s drift. To augment its use, a new family of stochastic volatility price processes is also provided where the processes’ strict local martingale behavior can be characterized.