This paper develops a non-finite-difference-based method of American option pricing under stochastic volatility by extending the Geske-Johnson compound option scheme. The characteristic function of the underlying state vector is inverted to obtain the vector's density using a kernel-smoothed fast Fourier transform technique. The method produces option values that are closely in line with the values obtained by finite-difference schemes. It also performs well in an empirical application with traded S&P 100 index options. The method is especially well suited to price a set of options with different strikes on the same underlying asset, which is a task often encountered by practitioners. Abstract This paper develops a non-…nite-di¤erence-based method of American option pricing under stochastic volatility by extending the Geske-Johnson compound option scheme. The characteristic function of the underlying state vector is inverted to obtain the vector's density using a kernel-smoothed fast Fourier transform technique. The method produces option values that are closely in line with the values obtained by …nite-di¤erence schemes. It also performs well in an empirical application with traded S&P 100 index options. The method is especially well suited to price a set of options with di¤erent strikes on the same underlying asset, which is a task often encountered by practitioners.
We investigate the effectiveness of initiating deposit insurance at the outset of a banking crisis. Using a conjoint analysis approach that allows us to consider the simultaneous impact of multiple deposit insurance attributes and various counterfactuals, we ask a multinational sample of respondents how they would view hypothetical account profiles following the failure of a large competing bank. Previous experience matters: respondents from countries without explicit deposit insurance exhibit greater withdrawal risk, suggesting that the introduction of deposit insurance during a crisis may be only partially successful in preventing bank runs. They also impose a higher deposit interest rate premium. Having a long-term bank relationship reduces withdrawal risk, as does the absence of co-insurance. Keywordsdeposit insurance, banking crises, bank run, conjoint analysis Disciplines Behavioral Economics | FinanceComments NOTICE: this is the author's version of a work that was accepted for publication in Journal of Financial Intermediation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Financial Intermediation, [24, 4, (2015) NOTICE: this is the author's version of a work that was accepted for publication in Journal of Financial Intermediation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Financial Intermediation, [24, 4, (2015)] doi:10.1016/j.jfi.2015.02.001 THE IMPACT OF DEPOSIT INSURANCE ON DEPOSITOR BEHAVIOR DURING A CRISIS: A CONJOINT ANALYSIS APPROACH AbstractWe investigate the effectiveness of initiating deposit insurance at the outset of a banking crisis.Using a conjoint analysis approach that allows us to consider the simultaneous impact of multiple deposit insurance attributes and various counterfactuals, we ask a multinational sample of respondents how they would view hypothetical account profiles following the failure of a large competing bank. Previous experience matters: respondents from countries without explicit deposit insurance exhibit greater withdrawal risk, suggesting that the introduction of deposit insurance during a crisis may be only partially successful in preventing bank runs. They also impose a higher deposit interest rate premium. Having a long-term bank relationship reduces withdrawal risk, as does the absence of co-insurance.
We investigate factors affecting the duration of eating and food preparation among adults in single decisionmaker households. Eating time is differentiated into primary and secondary eating time and further differentiated by location: at home vs. away from home. We construct a simple theoretical model, based on Becker's household production approach, to motivate empirical equations for eating and food preparation time. Empirical analysis is performed using data from the 2006-2008 Eating and Health (EH) Module of the American Time Use Survey (ATUS). Higher food-at-home prices are found to be associated with more time in food preparation and primary eating at home. Higher fast food prices are associated with more time in food preparation and less time in primary eating at home. We conclude that food prices influence home production and time allocation decisions. We also find that low-income adults spend more time in food preparation and primary eating at home and are less likely to eat away from home than those with more income. The presence of children in the household is associated with more time in food preparation and less time in primary eating away from home. Public policies attempting to effect an increase in food preparation among low-income, single adult households with children may need to account for limited opportunities such households can have to acquire and prepare healthier foods when additional time is required. AbstractWe investigate factors affecting the duration of eating and food preparation among adults in single decision-maker households. Eating time is differentiated into primary and secondary eating time and further differentiated by location: at home vs. away from home. We construct a simple theoretical model, based on Becker's household production approach, to motivate empirical equations for eating and food preparation time. Empirical analysis is performed using data from the 2006-2008 Eating and Health (EH) Module of the American Time Use Survey (ATUS). Higher food-at-home prices are found to be associated with more time in food preparation and primary eating at home. Higher fast food prices are associated with more time in food preparation and less time in primary eating at home. We conclude that food prices influence home production and time allocation decisions. We also find that low-income adults spend more time in food preparation and primary eating at home and are less likely to eat away from home than those with more income. The presence of children in the household is associated with more time in food preparation and less time in primary eating away from home. Public policies attempting to effect an increase in food preparation among low-income, single adult households with children may need to account for limited opportunities such households can have to acquire and prepare healthier foods when additional time is required.
We investigate the effects of parents, best friends, and relative prices on fruit and vegetable consumption by African American youths using behavioral data from the Family and Community Health Study and area-specific food prices from the Quarterly Food-at-Home Price Database. We construct a simultaneous equation ordered probit model that accounts for social interactions in fruit and vegetable consumption and specific aspects of the available food intake data. We estimate statistically significant endogenous consumption effects between a youth and a parent. Lower relative prices tend to increase intakes, particularly in the case of vegetables; however, the statistical significance of these effects is marginal. The results indicate the existence of social multipliers in fruit and vegetable consumption in African American families. The presence of these multipliers supports the design of youth-parent-based interventions to increase fruit and vegetable intake by African Americans. Additionally, intake also may be increased through relative price reductions.
The U.S. Department of Agriculture operates several food assistance programs aimed at alleviating food insecurity. We study whether participation in both participation in both SNAP and WIC alleviates food insecurity compared with participation in SNAP alone. We bound underlying causal effects by applying nonparametric treatment effect methods that allow for endogenous selection and underreported program participation when validation data are available for one program (treatment) but not the other. We estimate average treatment effects using data from the National Household Food Acquisition and Purchase Survey (FoodAPS). FoodAPS includes administrative data to validate SNAP participation. Information on local food prices allows us to construct a food expenditure‐based monotone instrumental variable that does not require a typical instrumental variable exclusion restriction. Under relatively weak monotonicity assumptions, we identify that the impact of participating in both programs relative to SNAP alone is strictly positive, suggesting that the programs are nonredundant. This evidence can support improved design and targeting of food programs.
USDA operates several food assistance programs aimed at alleviating food insecurity. Little is known about how they interact. We focus on SNAP and WIC, two of the largest means-tested programs that provide resources to low-income households to purchase food and differ in several respects. Our question is the extent to which participation in both programs alleviates food insecurity compared with participation in SNAP alone. We bound underlying causal effects by applying nonparametric treatment effect methods that allow for endogenous selection and underreported program participation to data from the National Household Food Acquisition and Purchase Survey (FoodAPS). FoodAPS contains administrative data to validate SNAP participation and data on the local food environment, including the cost of food, allowing us to tighten bounds on the causal effects. Under relatively weak assumptions about the selection process, combined with a food expenditure-based monotone instrumental variable, we identify that the marginal impact of participating in both programs is strictly positive. This finding provides evidence that the programs are nonredundant, which can aid policymakers in improving the design and targeting of food assistance programs. The methods showcase what can be learned about treatment effects when validation data are available for one program but not the other.
The optimal balance between keeping marriages intact, despite spousal conflict, and allowing for divorce is a subject of policy debate in the United States. To explore the trade-offs, I construct a structural model with information asymmetries, which may generate inefficient outcomes. Parameters are estimated using data from the National Survey of Families and Households. I find that eliminating separation periods decreases the conflict rate by 9.2% of its baseline level and increases the divorce rate by 4.0%. Perfect child support enforcement decreases the frequency of conflict and divorce by 2.7% and 21.2%, respectively, and reduces the incidence of inefficient divorces. Disciplines Economics CommentsThis is an article from Journal of Labor Economics 30 (2012) The optimal balance between keeping marriages intact, despite spousal conflict, and allowing for divorce is a subject of policy debate in the United States. To explore the trade-offs, I construct a structural model with information asymmetries, which may generate inefficient outcomes. Parameters are estimated using data from the National Survey of Families and Households. I find that eliminating separation periods decreases the conflict rate by 9.2% of its baseline level and increases the divorce rate by 4.0%. Perfect child support enforcement decreases the frequency of conflict and divorce by 2.7% and 21.2%, respectively, and reduces the incidence of inefficient divorces.
This paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMM-type estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual US stock return data over the course of 2000-2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect. KeywordsIdiosyncratic voltality, idiosyncratic voltality premium, cross-section of stock returns, generalized method of moments Disciplines Econometrics | Growth and Development | Other EconomicsComments NOTICE: this is the author's version of a work that was accepted for publication in Journal of Banking & Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Banking & Finance, [37, 8, (2013) AbstractThis paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMMtype estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual U.S. stock return data over the course of 2000-2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect.JEL classification: G12, C21
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