How domestic tasks are shared among household members is an important issue because the time women spent on housework translates to time spent not acquiring valuable skills and experience that enhance aspects of women’s lives which are external to the family such as their career and political involvement. This paper studies the effects of the distribution of intra-household bargaining power on families’ time allocation using cooperative bargaining model. I hypothesize that the wife’s time spent doing domestic chores is directly proportional to her relative bargaining power in the family. I test this hypothesis using instrumental variable approach —I exploit the enactment of equitable distribution of marital property in Florida in 1988 as a natural experiment which redistributes bargaining power while holding household’s preference and price constant. This method overcomes the problem of simultaneous causal relationship between family’s time allocation and household’s characteristics such as wife’s wage. Prior to the law enactment, marital property was divided according to the name on the property title which is disadvantageous to women who generally earn less than their husbands. Thus, the enactment of equitable distribution of property in divorce increases women’s bargaining powers by improving their prospects outside marriage. They can use the ‘threat’ of leaving the marriage as leverage when negotiating with their partners to do less housework. Other literature which studies the intra-household bargaining process focuses on the effects of a shift in bargaining power on married women’s labor supply and family’s expenditure on physical goods such as clothing. Instead of replicating previous research, I instead examine the effects of a change in the bargaining position of each spouse on their allocation of non-market labor time. I anticipate that after the enactment of equitable distribution of marital property statute, the allocation of household chores between the partners becomes more equal.

Conventional wisdom holds that interregional migration of labor is a stabilizing mechanism for unemployment and wages. For example, labor supply will increase in a high-wage region, as people migrate into that region seeking better compensation; this pushes down wages in the receiving region. However, less often noted is the idea that in-migration may also raise the demand for labor. High rates of population growth will spur demand for housing, infrastructure, services, and other durable nontradables. This increase in demand can, in the short and moderate run, be greater than the increase in supply, which spurs accelerating waves of further in-migration to fill those demands. I focus on this aspect of labor migration, and hypothesize that in the United States from 2000 onwards, both new residential construction and thus the demand for labor in rapidly growing U.S. metropolitan statistical areas (MSAs) were significantly and positively affected by in-migration; additionally, I posit that MSAs with higher in-migration during the decade were more severely impacted once migration stopped. I statistically test these hypotheses, adapting a study by Gonzalez and Ortega on the impact of international migration on Spanish regional economies over the last decade. My regression models, estimating the change in housing prices and change in residential construction in response to migration, add insights from urban economics and investment accelerator theory to the factors used in the Spanish study. I then test these models using data calculated or obtained from the U.S. Census Bureau and the Internal Revenue Service. The central question I seek to answer is whether, in the short to medium run, migration is a stabilizing or destabilizing factor in regional labor markets.

In this presentation I will argue that regardless of whether owned by the state, private capital or publicly traded on Chinese stock exchanges, Chinese corporations doing business outside of China inevitably become instruments of China's foreign policy. In a feedback loop in which both the state and the enterprise benefit (sometimes in counter-intuitive ways), the actions and fates of corporation and state become inextricably linked in a way that could not be replicated outside the unique world of "capitalism with Chinese characteristics". From the alleged links between telecommunications equipment manufacturer Huawei and the People’s Liberation Army to the official designation of Chinese IT industry hero Lenovo as a foreign-owned enterprise within China, divining the precise ownership of Chinese firms presents a Gordian knot to international customers and governments alike, encouraging suspicion and nationalist rhetoric in response to Chinese contract bids in developed economies, while simultaneously paving the way to lucrative deals in developing nations. But what does Chinese state support for industry really mean for non-Chinese trans-national firms? What is the significance of the state-encouraged acquisition spree that has seen Chinese firms purchase IBM’s PC business, Volvo and the firm that manufacturers London’s iconic black cabs, among others? How should other trans-national firms compete with Chinese bids for major international infrastructure projects and what is really at stake beyond the initial projects in question? This presentation, based upon an examination of the ownership and activities of Chinese firms competing in international business, will offer an alternative lens through which to view the international activities of Chinese enterprises, suggesting that to truly evaluate the potential profit and loss of any specific commercial activity one must first look beyond the letterhead.

Governments can manipulate reports of the inflation rate to hide economic problems, and to generate revenues from the hidden depreciation of their liabilities valued in domestic currency. However, such practices are unpopular and generally short-lived because citizens soon recognize the loss in their purchasing power. Previously, I constructed an alternative price index for 2006 to 2008 and found that the National Statistics and Censuses Institute underreported the official inflation rate since February 2007. My data, used in conjunction with other alternative indexes, showed that the reported Consumer Price Index (CPI) only accounted for between a half and a third of the real inflation rate. This project explores effects of underreporting inflation in Argentina, and provides further evidence to support the existence of manipulation in the official statistics reports. Using the alternative price indexes, I estimated government gains from domestic bonds and the social security system due to the misreported inflation rates since the manipulation began. By reporting a CPI that is lower than the real one, the government was able to finance its expenditures at a decreasing real cost, at the expense of private investors and citizens. My preliminary results show that the Argentinian government profited in real terms from issuing bonds, and maintained a moderately low budget deficit despite increasing the number of social security beneficiaries. I also studied the national accounts and central bank publications of the last decade and observed a surprisingly high rate of nominal growth beginning in 2007. I will demonstrate that this unexpected rise can be explained by the discrepancy between the reported and the real inflation rate. Since 2009, the Argentinian government has actively censored independent domestic studies on the official CPI, so for the time being, it is essential for foreign scholars to research and keep track of Argentina’s deteriorating statistics.

In housing markets at risk of natural disaster, amenities are positively correlated with risk. Hedonic analyses have been used to quantify the effect of natural-disaster risk on the housing market and reveal homeowners' risk information about susceptibility to natural disasters. However, hedonic analyses assume relationships are stationary, homogeneous, across space. To illustrate the consequences of non-stationary hedonic coefficients, we use a geographically-weighted regression to quantify the effect of wildfire risk on the housing market in Colorado Springs. Geographically-weighted regressions have been used to model spatial variation in fields like ecology, public health, sociology, and environmental management. In 2002, concerned about wildfire risk, the Colorado Springs Fire Department evaluated 35, 000 individual homes in Colorado Springs, CO for wildfire risk based on property characteristics. We find assuming spatial stationarity conceals policy-relevant information about the impact of the evaluation across homeowners.