1. Education

2. Career

3. Scholarships
    "Family and Government Insurance: Wage, Earnings, and Income Risks in the Netherlands and the US" (2019)  "The Lifetime Costs of Bad Health" (2018)  "The Aggregate Implications of Gender and Marriage" (2018)  "Inequality and Recessions" (2018)  "End-of-life medical spending in last twelve months of life is lower than previously reported" (2017)  "Why do the elderly save? The role of medical expenses" (2010)  "Entrepreneurship, Frictions, and Wealth" (2006)  "Wealth inequality: Data and models" (2008) 

4. References

5. External links

Education

Mariacristina De Nardi received her B.A. in Economics and Commerce with the highest marks and honours from Ca' Foscari University of Venice, Italy, in November 1993.^[5] She then proceeded to the University of Chicago, where she got her M.A. in June 1998 and then her Ph.D. in August 1999.^{[6] [7]}

Career

De Nardi currently works as a Senior Scholar at the Opportunity and Inclusive Growth Institute in the research department at the Federal Reserve Bank of Minneapolis since September 2018. Since 2013, she has been an Economics Professor at University College London. De Nardi is also a Faculty Research Fellow at the National Bureau of Economic Research since 2006 and a International Research Fellow at the Institute of Fiscal Studies since 2015. She has also been a Research Fellow at the Center for Economic and Policy Research since 2016. In 2018, she became the First Vice President for the Midwest Economic Association. ^[8] De Nardi is a Coordinator and leader in the Market Network at Human Capital and Economic Opportunity (HCEO). Before moving to the Federal Reserve Bank of Minneapolis in 2018, De Nardi was a Senior Economist and Research Advisor in the research department at the Federal Reserve Bank of Chicago.^[9] De Nardi was an Assistant Professor in the Department of Economics at the University of Minnesota from 2000-2005. She first started working at the Federal Reserve Bank of Chicago as an Economist in 1998. De Nardi worked as an Research Assistant to Professor Thomas J. Sargent. Before getting her M.A. at the University of Chicago, she was a teaching assistant there. After getting her B.A., De Nardi become a Research Fellow at Ca' Foscari University of Venice.^[10]

De Nardi is currently an editor for Review of Economic Dynamics since 2017. ^[11] Since 2015, she has been on the Board of Editors for Journal of Economic Literature. ^[12] During 2014-2017, De Nardi was Associate Editor for both the Journal of the European Economic Association and Fiscal Studies.^[13]

Scholarships

Mariacristina De Nardi’s is the author of over 30 papers. De Nardi's work include: examining the role of bequests and entrepreneurship to explain the wealth distribution; studying the medical spendings of the elderly and looking at how they save; examining how the Social Security reform effects the aggregate economy; studying the relationship between fertility and Social Security; looked into the effects of estate taxation and much more.^[14]

"Family and Government Insurance: Wage, Earnings, and Income Risks in the Netherlands and the US" (2019)

De Nardi co-authored this article with Giulio Fella, Marike Knoef, Gonzalo Paz-Pardo and Raun Van Ooijen. De Nardi, Fella, Knoef, Paz-Pardo and Van Ooijen looks into the size and distribution of wage shocks and the role of insurance mechanisms against these shocks in both the United States and the Netherlands. This paper builds on other papers written previously but, unlike which explored shocks in individual earnings, De Nardi, Fella, Knoef, Paz-Pardo and Van Ooijen distinguished shocks in wages and changes in hours worked. First, they documented data on the distribution of male wages and earnings and their household earnings and incomes found by analyzing distributional measures of wage changes. The results from the analysis showed that in both the Netherlands and the United states, there was evidence of non-linearity and age dependence, with high wage and earnings risk for the people with lowest and highest wage and earnings. Both Countries showed that wage and earnings persistence varied significantly by age. In the Netherlands, evidence showed that income risk is lower for the middle of the income distribution. De Nardi, Fella, Knoef, Paz-Pardo and Van Ooijen found that the government plays a large role in reducing risk in the Netherlands. While, in the United States, the role of the family in reducing risk is more important. They looked into how much insurance was provided by spousal labor supply by comparing individual earnings to total earnings at the household level. They also looked into how much insurance was provided by the tax and transfer system. De Nardi, Fella, Knoef, Paz-Pardo and Van Ooijen compared the two countries. They concluded that the labor supply has little effect the standard deviation of wage in the Netherlands. Instead, they found that taxes and transfers have a bigger effect in the Netherlands and they reduce inequality and risk in wages and earnings. In the United States, the standard deviation of all income measures were generally higher. There was evidence of volatility in hours that increased the dispersion in wage changes in the United States. The standard deviation of male earnings were seen to be higher than previously. Unlike the Netherlands, the United States spousal labor supply played a bigger role in reducing standard deviation of male earnings over all levels of previous earnings. In the Netherlands, that role was on the government.^[15]

"The Lifetime Costs of Bad Health" (2018)

Bad health can lower ones’ life expectancy. This article queries the effects of health shocks over the life-cycle. Co-authored with Svetlana Pashchenko and Ponpoke Porapakkarm, with data, they developed a structural framework to help measure the long-run effects of bad health. They took the fact that inequality can be traced back to factors predetermined early in life into consideration and created a structural model that is able to give short and long run dynamics of health and health related inequality of economic outcomes to help measures the lifetime costs of bad health. For their research, De Nardi, Pashchenko and Porapakkarm used three data sets: the Health and Retirement Study, the Medical Expenditure Panel and Survey and the Panel Study of Income Dynamics. They found that generally, individuals were only willing to pay approximately 5 percent of the average income to increase their probability of being healthy by one percent. The authors state that the monetary costs of being unhealthy are very concentrated and highly unequally distributed across health types. People with bad health have a lower tendency to save. So the difference between health and unhealthy people is a factor to explaining the large gap in wealth due to health. De Nardi, Pashchenko and Porapakkarm conclude that bad health only explains approximately 47 percent of the variation in lifetime utilities.^[16]

"The Aggregate Implications of Gender and Marriage" (2018)

Margherita Borella, Mariacristina De Nardi, Fang Yang investigate the aggregate importance of gender and marriage. They note that most macroeconomists ignore women and marriage when setting up structural models and calibrating them using data on men only. Borella, De Nardi, Yang question if by ignoring gender and marriage in both models and data, does that imply the resulting calibration matches well the key economic aggregates. Using data from the Panel Study and Income Dynamics and the Health and Retirement Survey for the 1941-1945 cohort. In their paper, they constructed and calibrated four different economies. Economy 1 uses a standard one-gender, no marriage, lifecycle framework and like usual macro models, they only used data on men for calibration. While Economy 2 is the same model as Economy 1 but instead they calibrated using data on both women and men. Economy 3 uses the same model as both Economy 1 and 2 but now its calibrated by aggregating the data at the household level and using couples instead of singles. Finally, in Economy 4, the model single and married men and women over their whole life cycle. They found that Economy 4 does better than the other economies. Which shows that modelling marriage and gender is important for understanding key economic aggregates over the life cycle. Borella, De Nardi, Yang conclude that macroeconomists should be taking marriage and gender into account in the quantitative structural models. They state that by modelling marriage and gender explicitly would give the best results for matching the aggregates.^[17]

"Inequality and Recessions" (2018)

In this article, Gene Amromin, Mariacristina De Nardi, Karl Schulze question if the widening gap between the rich and poor has any direct effects on macroeconomic aggregates. They largely focus on the Great Recession.Using the Panel Study of Income Dynamics and Credit Bureau Panel Data, they compare consumption and wealth during the Great Recession. Amromin, De Nardi and Schulze argue that the role of borrowing constraints cannot be fully captured by only looking at data where the majority of households have little wealth before the recession. They state that most macroeconomic theories do this. Summarizing two papers, one by Krusell and Smith and another by Krueger, Mitman and Perri. Which provide evidence to show that inequality can make the effects of a recession even worse. Amromin, De Nardi and Schulze conclude that different measures of household constraints have permanently increased due to the Great Recession.^[18]

"End-of-life medical spending in last twelve months of life is lower than previously reported" (2017)

Collaborating with 27 other economists, they measured the composition and magnitude of medical spending in the last three years before death. Taking health care data from nine countries: Denmark, England, France, Germany, Japan, the Netherlands, Taiwan, United States and Canada(Quebec). The comparison between countries revealed that there is no direct relationship between how a country's health care service are funded and how they are provided. They found the average medical spending per capita in the last twelve months of life is about $80,000 in the United States, $60,000 in the Netherlands and Denmark and $50,000 in Germany. Medical spending in the last twelve months and last three years of life is high. De Nardi, French, et al. recorded that in the last twelve months of life, medical spending ranged from 8.2 percent in Japan to 22.7 percent in Quebec. Since Hospital spendings make a significant portion of medical spendings in the last twelve months compared to the last three years of life, they saw the medical spendings ranging from 13.5 percent in Japan to 34.9 percent in Taiwan win the last three years of life. They concluded that all nine countries they look into, the medical spendings at the end of life were high compared to spending at other ages. In the last twelve months of life, they saw medical spending making up most of its aggregate spending. In the United States, it was about 8.5 percent and 11.2 percent in Taiwan. The reduction of medical spending would does not effect the total medical spending significantly. De Nardi, French, et al. concluded that instead there should be a reduction of cost in caring for people with chronic conditions.^[19]

"Why do the elderly save? The role of medical expenses" (2010)

This paper by Mariacristina De Nardi, Eric French and John Bailey Jones construct a model of saving for retired singles that include a mix of different medical expenses and life expectancy. For their paper, they used the Assets and Health Dynamics of the Oldest Old dataset (AHEAD). De Nardi, French and Jones only took the data on single retired individuals for their analysis. Which consisted of 3,259 individuals, where 592 were men and 2,667 were women. For their model, they accounted for social insurance programs. Their estimated model shows that the savings of the elderly are largely due medical expenditures. De Nardi, French and Jones predict that the elderly, between the ages of 74 and 84, the median assets for those in the top permanent income quantile see a fall from $170,000 to $130,000. If all medical expenses were to be eliminated, the median asset would fall much more. We would expect it to fall from $170,000 to $80,000. Their results are mainly due to two things. First, even if the elderly had health insurance, the out-of-pocket medical and nursing home expense are still a large amount. Second, they found that the average medical cost rises significantly with age and income. Their model predicts the average out-of-pocket medical expenses will rise from $1,100 when they are 75 to $9,200 when they are 95. They also found that, a 95 year old in the top quintile of the permanent income distribution is to spend $15,800 on medical expenses. While someone thats the same age but in the bottom quintile of the permanent income distribution is expected to spend $1,700. So medical spending largely effects savings. By properly accounting for old age expenditure on medical care and social insurance programs providing a consumption floor, it can explain the elderly's savings. De Nardi, French and Jones conclude that savings of the elderly are motivated by the medical expenditures and that social insurance affects the saving of both the income-rich and income-poor.^[20]

"Entrepreneurship, Frictions, and Wealth" (2006)

Mariacristina received a research grant from the National Science Foundation Research Grant. She is the principal investigator and started researching from 2003-2006.

De Nardi co-authored this journal article with Marco Cagetti. De Nardi and Cagetti constructed a model that analyzes the role of borrowing constraints as determinants of entrepreneurial choices and the effects it has on wealth inequality and aggregate capital accumulation. They found that more restrictive borrowing constraints created less inequality in wealth holdings but causes a reduction in average firm size, number of entrepreneurs and aggregate capital accumulation. Cagetti and De Nardi show the relationship between entrepreneurship and wealth. From their data, they explain how entrepreneurs are richer than non-entrepreneurs but business owners are much richer than self-employers. The paper notes that many entrepreneurs have potentially high rates of return but are constrained in the amount they can borrow. Since an entrepreneurs wealth acts as collateral, the amount that can be borrowed is determined by how rich they are. Cagetti and De Nardi used the assumption where if there is a borrowing constraint, entrepreneurs could sell their idea to someone else that faces less constraint. They show how the main factor in determining the number of entrepreneurs, size of firm, aggregate capital accumulation and overall wealth concentration in the population is due to how stringent the borrowing constraint is and voluntary bequest. They concluded that the main factors can cause issues for policy analysis, such as subsidized loans and taxing bequest. The paper notes that taxing bequest can reduce the amount of entrepreneurial wealth, which affects the amount they can borrow. Resulting in less entrepreneurs.^[21]

"Wealth inequality: Data and models" (2008)

Mariacristina De Nardi collaborated with Marco Cagetti to summarize the wealth distribution and its economic models in the United States. The majority of the data they used are from the Survey of Consumer Finances. Cagetti and De Nardi explain that all quantitative models of wealth inequality make human capital exogenous and they argue that we should actually take human capital accumulation into consideration when studying savings and wealth inequality. They also point out that some areas in models of inequality can be employed and extended. Cagetti and De Nardi states that it takes a lot of work to fully understand the quantitative importance of each factor in determining wealth inequality. Though there has been great advances in the models, there is still room for improvement in these models in order to apply them to problems where inequality is a key determinant.^[22]

References

External links

• [https://scholar.google.com/citations?user=WyQ14q4AAAAJ&hl=en Google Scholar profile]

• 1904-05 MHA season
• 1904-05 Michigan State Normal men's basketball team
• 1904-05 Michigan State Normal Normalites men's basketball team
• 1904-05 Michigan State Spartans men's basketball team
• 1904-05 Northern Football League
• 1904-05 Penn State Nittany Lions basketball team
• 1904-05 Penn State Nittany Lions men's basketball team
• 1904-05 Port Vale F.C. season
• 1904-05 Primera División de México
• 1904-05 Primera Fuerza season
• 1904-05 Real Madrid CF season
• 1904-05 Rugby Union County Championship
• 1904-05 Scottish Division One
• 1904-05 Scottish Division Two
• 1904-05 Sheffield Shield season
• 1904-05 Syracuse Orangemen basketball team
• 1904-05 Syracuse Orangemen men's basketball team
• 1904-05 Welsh Amateur Cup
• 1904-05 West Virginia Mountaineers men's basketball team
• 1904-05 Wisconsin Badgers men's basketball team
• 1904-05 Woolwich Arsenal F.C. season
• 1904-1905 Welsh revival
• 1904 AD
• 1904 Alabama Crimson White football
• 1904 Alabama Crimson White football season