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- Penalized sieve minimum distance (5)
- Asymptotic distribution (3)
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- Conditional heteroskedasticity (3)
- Dynamic mechanism design (3)
- Experimental gaming (3)
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- Long memory (3)
- Modulus of continuity (3)
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- Sequential investment (3)
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- Asymptotic power (2)
- Bayesian learning (2)
- Bootstrap (2)
- Censored regression (2)
- Climate change (2)
- Coase conjecture (2)
- Cointegration (2)
- Common knowledge (2)
- Compensated separability (2)
- Consistency (2)
- Convergence rate (2)
Articles 31 - 60 of 69
Full-Text Articles in Social and Behavioral Sciences
Affective Decision Making And The Ellsberg Paradox, Anat Bracha, Donald J. Brown
Affective Decision Making And The Ellsberg Paradox, Anat Bracha, Donald J. Brown
Cowles Foundation Discussion Papers
We characterize, in the framework for variational preferences, the affective decision making model of choice under risk and uncertainty introduced by Bracha and Brown (2007). This characterization (i) provides a rigorus decision-theoretic foundation for affective decision making, (ii) offers an axiomatic explanation for ambiguity-seeking in the Ellsberg Paradox and (iii) suggests a dual representation of ADM games in terms of the Legendre-Fenchel conjugate.
Affective Decision Making And The Ellsberg Paradox, Anat Bracha, Donald J. Brown
Affective Decision Making And The Ellsberg Paradox, Anat Bracha, Donald J. Brown
Cowles Foundation Discussion Papers
Affective decision-making is a strategic model of choice under risk and uncertainty where we posit two cognitive processes — the “rational” and the “emotional” process. Observed choice is the result of equilibrium in this intrapersonal game. As an example, we present applications of affective decision-making in insurance markets, where the risk perceptions of consumers are endogenous. We derive the axiomatic foundation of affective decision making, and show that affective decision making is a model of ambiguity-seeking behavior consistent with the Ellsberg paradox.
Estimating Derivatives In Nonseparable Models With Limited Dependent Variables, Joseph G. Altonji, Hidehiko Ichimura, Taisuke Otsu
Estimating Derivatives In Nonseparable Models With Limited Dependent Variables, Joseph G. Altonji, Hidehiko Ichimura, Taisuke Otsu
Cowles Foundation Discussion Papers
We present a simple way to estimate the effects of changes in a vector of observable variables X on a limited dependent variable Y when Y is a general nonseparable function of X and unobservables, and X is independent of the unobservables. We treat models in which Y is censored from above, below, or both. The basic idea is to first estimate the derivative of the conditional mean of Y given X at x with respect to x on the uncensored sample without correcting for the effect of x on the censored population. We then correct the derivative for the …
Smoothing Local-To-Moderate Unit Root Theory, Peter C.B. Phillips, Tassos Magdalinos, Liudas Giraitis
Smoothing Local-To-Moderate Unit Root Theory, Peter C.B. Phillips, Tassos Magdalinos, Liudas Giraitis
Cowles Foundation Discussion Papers
A limit theory is established for autoregressive time series that smooths the transition between local and moderate deviations from unity and provides a transitional form that links conventional unit root distributions and the standard normal. Edgeworth expansions of the limit theory are given. These expansions show that the limit theory that holds for values of the autoregressive coefficient that are closer to stationarity than local (i.e. deviations of the form = 1 + (c/n), where n is the sample size and c < 0) holds up to the second order. Similar expansions around the limiting Cauchy density are provided for the mildly explosive case.
Unit Root Model Selection, Peter C.B. Phillips
Unit Root Model Selection, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Some limit properties for information based model selection criteria are given in the context of unit root evaluation and various assumptions about initial conditions. Allowing for a nonparametric short memory component, standard information criteria are shown to be weakly consistent for a unit root provided the penalty coefficient C n → ∞ and C n /n → 0 as n → ∞. Strong consistency holds when C n /(log log n ) 3 → ∞ under conventional assumptions on initial conditions and under a slightly stronger condition when initial conditions are infinitely distant in the unit root model. The limit …
Unit Root And Cointegrating Limit Theory When Initialization Is In The Infinite Past, Peter C.B. Phillips, Tassos Magdalinos
Unit Root And Cointegrating Limit Theory When Initialization Is In The Infinite Past, Peter C.B. Phillips, Tassos Magdalinos
Cowles Foundation Discussion Papers
It is well known that unit root limit distributions are sensitive to initial conditions in the distant past. If the distant past initialization is extended to the infinite past, the initial condition dominates the limit theory producing a faster rate of convergence, a limiting Cauchy distribution for the least squares coefficient and a limit normal distribution for the t ratio. This amounts to the tail of the unit root process wagging the dog of the unit root limit theory. These simple results apply in the case of a univariate autoregression with no intercept. The limit theory for vector unit root …
Long Memory And Long Run Variation, Peter C.B. Phillips
Long Memory And Long Run Variation, Peter C.B. Phillips
Cowles Foundation Discussion Papers
A commonly used defining property of long memory time series is the power law decay of the autocovariance function. Some alternative methods of deriving this property are considered working from the alternate definition in terms of a fractional pole in the spectrum at the origin. The methods considered involve the use of (i) Fourier transforms of generalized functions, (ii) asymptotic expansions of Fourier integrals with singularities, (iii) direct evaluation using hypergeometric function algebra, and (iv) conversion to a simple gamma integral. The paper is largely pedagogical but some novel methods and results involving complete asymptotic series representations are presented. The …
Optimal Bandwidth Choice For Interval Estimation In Gmm Regression, Yixiao Sun, Peter C.B. Phillips
Optimal Bandwidth Choice For Interval Estimation In Gmm Regression, Yixiao Sun, Peter C.B. Phillips
Cowles Foundation Discussion Papers
In time series regression with nonparametrically autocorrelated errors, it is now standard empirical practice to construct confidence intervals for regression coefficients on the basis of nonparametrically studentized t -statistics. The standard error used in the studentization is typically estimated by a kernel method that involves some smoothing process over the sample autocovariances. The underlying parameter ( M ) that controls this tuning process is a bandwidth or truncation lag and it plays a key role in the finite sample properties of tests and the actual coverage properties of the associated confidence intervals. The present paper develops a bandwidth choice rule …
Pareto Improving Taxes, John Geanakoplos, Heracles M. Polemarchakis
Pareto Improving Taxes, John Geanakoplos, Heracles M. Polemarchakis
Cowles Foundation Discussion Papers
We show that in almost every economy with separable externalities, every competitive equilibrium can be Pareto improved by a package of anonymous commodity taxes that causes prices to adjust and markets to reclear at different levels of individual consumption. This constrained suboptimality of competitive allocations might provide a rationale for economic policy in economies with externalities. It shows that policy makers should look for good tax packages that help everybody, rather than thinking taxes must inevitably be bad for some lobby that will oppose them.
Overlapping Generations Models Of General Equilibrium, John Geanakoplos
Overlapping Generations Models Of General Equilibrium, John Geanakoplos
Cowles Foundation Discussion Papers
The OLG model of Allais and Samuelson retains the methodological assumptions of agent optimization and market clearing from the Arrow-Debreu model, yet its equilibrium set has different properties: Pareto inefficiency, indeterminacy, positive valuation of money, and a golden rule equilibrium in which the rate of interest is equal to population growth (independent of impatience). These properties are shown to derive not from market incompleteness, but from lack of market clearing “at infinity;” they can be eliminated with land or uniform impatience. The OLG model is used to analyze bubbles, social security, demographic effects on stock returns, the foundations of monetary …
Reforming Social Security With Progressive Personal Accounts, John Geanakoplos, Stephen P. Zeldes
Reforming Social Security With Progressive Personal Accounts, John Geanakoplos, Stephen P. Zeldes
Cowles Foundation Discussion Papers
The heated debate about how to reform Social Security has come to a standstill because the view of most Democrats (that Social Security must be a defined benefits plan similar in spirit to the current system) seems irreconcilable with the proposals supported by many Republicans (to create a defined contribution system of personal accounts holding marketed assets). We describe a system of “progressive personal accounts” that preserves the core goals of both parties, and that is self-balancing on an ongoing basis. Progressive personal accounts have two critical features: (1) accruals into the personal accounts would be exclusively in a new …
Semiparametric Cointegrating Rank Selection, Xu Cheng, Peter C.B. Phillips
Semiparametric Cointegrating Rank Selection, Xu Cheng, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Some convenient limit properties of usual information criteria are given for cointegrating rank selection. Allowing for a nonparametric short memory component and using a reduced rank regression with only a single lag, standard information criteria are shown to be weakly consistent in the choice of cointegrating rank provided the penalty coefficient C n → ∞ and C n /n → 0 as n → ∞. The limit distribution of the AIC criterion, which is inconsistent, is also obtained. The analysis provides a general limit theory for semiparametric reduced rank regression under weakly dependent errors. The method does not require the …
Nonlinearity And Temporal Dependence, Xiaohong Chen, Lars P. Hansen, Marine Carrasco
Nonlinearity And Temporal Dependence, Xiaohong Chen, Lars P. Hansen, Marine Carrasco
Cowles Foundation Discussion Papers
Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models. We study this link using two notions of temporal dependence: beta-mixing and rho-mixing. We show that beta-mixing and rho-mixing with exponential decay are essentially equivalent concepts for scalar diffusions. For stationary diffusions that fail to be rho-mixing, we show that they are still beta-mixing except that the decay rates are slower than exponential. For such processes we find transformations of the Markov states that have finite variances but infinite spectral densities at frequency zero. Some have spectral densities that diverge at frequency zero in a manner …
Structural Nonparametric Cointegrating Regression, Qiying Wang, Peter C.B. Phillips
Structural Nonparametric Cointegrating Regression, Qiying Wang, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Nonparametric estimation of a structural cointegrating regression model is studied. As in the standard linear cointegrating regression model, the regressor and the dependent variable are jointly dependent and contemporaneously correlated. In nonparametric estimation problems, joint dependence is known to be a major complication that affects identification, induces bias in conventional kernel estimates, and frequently leads to ill-posed inverse problems. In functional cointegrating regressions where the regressor is an integrated time series, it is shown here that inverse and ill-posed inverse problems do not arise. Remarkably, nonparametric kernel estimation of a structural nonparametric cointegrating regression is consistent and the limit distribution …
Testing For Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood, Taisuke Otsu, Myung Hwan Seo, Yoon-Jae Whang
Testing For Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood, Taisuke Otsu, Myung Hwan Seo, Yoon-Jae Whang
Cowles Foundation Discussion Papers
We propose non-nested hypotheses tests for conditional moment restriction models based on the method of generalized empirical likelihood (GEL). By utilizing the implied GEL probabilities from a sequence of unconditional moment restrictions that contains equivalent information of the conditional moment restrictions, we construct Kolmogorov-Smirnov and Cramer-von Mises type moment encompassing tests. Advantages of our tests over Otsu and Whang’s (2007) tests are: (i) they are free from smoothing parameters, (ii) they can be applied to weakly dependent data, and (iii) they allow non-smooth moment functions. We derive the null distributions, validity of a bootstrap procedure, and local and global power …
Nonlinearity And Temporal Dependence, Xiaohong Chen, Lars P. Hansen, Marine Carrasco
Nonlinearity And Temporal Dependence, Xiaohong Chen, Lars P. Hansen, Marine Carrasco
Cowles Foundation Discussion Papers
Nonlinearities in the drift and diffusion coefficients influence temporal dependence in diffusion models. We study this link using three measures of temporal dependence: rho-mixing, beta-mixing and alpha-mixing. Stationary diffusions that are rho-mixing have mixing coefficients that decay exponentially to zero. When they fail to be rho-mixing, they are still beta-mixing and alpha-mixing; but coefficient decay is slower than exponential. For such processes we find transformations of the Markov states that have finite variances but infinite spectral densities at frequency zero. The resulting spectral densities behave like those of stochastic processes with long memory. Finally we show how state-dependent, Poisson sampling …
Local Limit Theory And Spurious Nonparametric Regression, Peter C.B. Phillips
Local Limit Theory And Spurious Nonparametric Regression, Peter C.B. Phillips
Cowles Foundation Discussion Papers
A local limit theorem is proved for sample covariances of nonstationary time series and integrable functions of such time series that involve a bandwidth sequence. The resulting theory enables an asymptotic development of nonparametric regression with integrated or fractionally integrated processes that includes the important practical case of spurious regressions. Some local regression diagnostics are suggested for forensic analysis of such regresssions, including a local R² and a local Durbin Watson (DW) ratio, and their asymptotic behavior is investigated. The most immediate findings extend the earlier work on linear spurious regression (Phillips, 1986), showing that the key behavioral characteristics of …
Estimation Of Nonparametric Conditional Moment Models With Possibly Nonsmooth Moments, Xiaohong Chen, Demian Pouzo
Estimation Of Nonparametric Conditional Moment Models With Possibly Nonsmooth Moments, Xiaohong Chen, Demian Pouzo
Cowles Foundation Discussion Papers
This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables. It is a problem of nonparametric nonlinear instrumental variables (IV) estimation, and a difficult nonlinear ill-posed inverse problem with an unknown operator. We first propose a penalized sieve minimum distance (SMD) estimator of the unknown functions that are identified via the conditional moment models. We then establish its consistency and convergence rate (in strong metric), allowing for possibly non-compact function parameter spaces, possibly non-compact finite or infinite dimensional sieves with flexible lower semicompact or …
Estimation Of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals, Xiaohong Chen, Demian Pouzo
Estimation Of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals, Xiaohong Chen, Demian Pouzo
Cowles Foundation Discussion Papers
This paper studies nonparametric estimation of conditional moment models in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a nonparametric nonlinear instrumental variables (IV) problem. We propose a class of penalized sieve minimum distance (PSMD) estimators which are minimizers of a penalized empirical minimum distance criterion over a collection of sieve spaces that are dense in the infinite dimensional function parameter space. Some of the PSMD procedures use slowly growing finite dimensional sieves with flexible penalties or without any penalty; some use large dimensional sieves with lower semicompact and/or convex penalties. …
The Impact Of A Hausman Pretest On The Size Of Hypothesis Tests, Patrik Guggenberger
The Impact Of A Hausman Pretest On The Size Of Hypothesis Tests, Patrik Guggenberger
Cowles Foundation Discussion Papers
This paper investigates the size properties of a two-stage test in the linear instrumental variables model when in the first stage a Hausman (1978) specification test is used as a pretest of exogeneity of a regressor. In the second stage, a simple hypothesis about a component of the structural parameter vector is tested, using a t -statistic that is based on either the ordinary least squares (OLS) or the two-stage least squares estimator (2SLS) depending on the outcome of the Hausman pretest. The asymptotic size of the two-stage test is derived in a model where weak instruments are ruled out …
Estimation Of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals, Xiaohong Chen, Demian Pouzo
Estimation Of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals, Xiaohong Chen, Demian Pouzo
Cowles Foundation Discussion Papers
This paper studies nonparametric estimation of conditional moment restrictions in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a nonparametric nonlinear instrumental variables (IV) problem. We propose a class of penalized sieve minimum distance (PSMD) estimators, which are minimizers of a penalized empirical minimum distance criterion over a collection of sieve spaces that are dense in the infinite dimensional function parameter space. Some of the PSMD procedures use slowly growing finite dimensional sieves with flexible penalties or without any penalty; others use large dimensional sieves with lower semicompact and/or convex penalties. …
Foundations Of Intrinsic Habit Formation, Kareen Rozen
Foundations Of Intrinsic Habit Formation, Kareen Rozen
Cowles Foundation Discussion Papers
We provide theoretical foundations for several common (nested) representations of intrinsic linear habit formation. These representations are dynamically consistent and additive, with geometrically decaying coefficients of habit formation. Our axiomatization introduces a revealed preference theory of weaning a decision-maker from her habits using the device of compensation. We characterize linear habit formation in terms of the ability to wean using uniquely determined compensating streams. Moreover, we distinguish between habits that are responsive to weaning and those that are persistent, develop a simple choice-theoretic measure of the rate of habit decay, and demonstrate how to recover the entire sequence of habit …
A ‘Dual’-Improved Shortcut To The Long Run, Kareen Rozen
A ‘Dual’-Improved Shortcut To The Long Run, Kareen Rozen
Cowles Foundation Discussion Papers
I use the theories of duality and optimal branchings to find a necessary and sufficient characterization of stochastically stable limit sets (SSLS) that helps improve the radius — modified coradius test of Ellison (2000). The improved shortcut I offer may permit the identification of SSLS when Ellison’s radius — modified coradius test fails to identify any, or may be able to pinpoint the true SSLS in cases where Ellison’s test identifies only a superset. I also demonstrate precisely why the radius — modified coradius test is not universally applicable and illuminate the connection between the modified coradius and the Lagrange …
Derivatives Markets For Home Prices, Robert J. Shiller
Derivatives Markets For Home Prices, Robert J. Shiller
Cowles Foundation Discussion Papers
The establishment recently of risk management vehicles for home prices is described. The potential value of such vehicles, once they become established, is seen in consideration of the inefficiency of the market for single family homes. Institutional changes that might derive from the establishment of these new markets are described. An important reason for these beginnings of real estate derivative markets is the advance in home price index construction methods, notably the repeat sales method, that have appeared over the last twenty years. Psychological barriers to the full success of such markets are discussed.
Limit Theorems For Functionals Of Sums That Converge To Fractional Brownian And Stable Motions, P. Jeganathan
Limit Theorems For Functionals Of Sums That Converge To Fractional Brownian And Stable Motions, P. Jeganathan
Cowles Foundation Discussion Papers
No abstract provided.
Emerging Markets In An Anxious Global Economy, Ana Fostel, John Geanakoplos
Emerging Markets In An Anxious Global Economy, Ana Fostel, John Geanakoplos
Cowles Foundation Discussion Papers
We provide a theory of pricing for emerging asset classes, like emerging markets, that are not yet mature enough to be attractive to the general public. Our model provides an explanation for the volatile access of emerging economies to international financial markets and for several stylized facts we identify in the data during the 1990’s. We present a general equilibrium model with incomplete markets and endogenous collateral and an extension encompassing adverse selection. We show that contagion, flight to liquidity and issuance rationing can occur in equilibrium during what we call global anxious times.
Understanding Sectoral Labor Market Dynamics: An Equilibrium Analysis Of The Oil And Gas Field Services Industry, Patrick Kline
Understanding Sectoral Labor Market Dynamics: An Equilibrium Analysis Of The Oil And Gas Field Services Industry, Patrick Kline
Cowles Foundation Discussion Papers
This paper examines the response of employment and wages in the US oil and gas field services industry to changes in the price of crude petroleum using a time series of quarterly data spanning the period 1972-2002. I find that labor quickly reallocates across sectors in response to price shocks but that substantial wage premia are necessary to induce such reallocation. The timing of these premia is at odds with the predictions of standard models-wage premia emerge quite slowly, peaking only as labor adjustment ends and then slowly dissipating. After considering alternative explanations, I argue that a dynamic market clearing …
Conflict Leads To Cooperation In Nash Bargaining, Kareen Rozen
Conflict Leads To Cooperation In Nash Bargaining, Kareen Rozen
Cowles Foundation Discussion Papers
We consider a multilateral Nash demand game where short-sighted players come to the bargaining table with requests for both coalition partners and the potentially generated resource. We prove that group learning leads with probability one to complete cooperation and a strictly self-enforcing allocation (i.e., in the interior of the core). Highlighting group dynamics, we demonstrate that behaviors which appear destructive can themselves lead to beneficial and strictly self-enforcing cooperation.
Foundations Of Intrinsic Habit Formation, Kareen Rozen
Foundations Of Intrinsic Habit Formation, Kareen Rozen
Cowles Foundation Discussion Papers
We provide theoretical foundations for several common (nested) representations of intrinsic linear habit formation. Our axiomatization introduces an intertemporal theory of weaning a decision-maker from her habits using the device of compensation. We clarify differences across specifications of the model, provide measures of habit-forming tendencies, and suggest methods for axiomatizing time-nonseparable preferences.
Semiparametric Efficiency In Gmm Models Of Nonclassical Measurement Errors, Missing Data And Treatment Effects, Xiaohong Chen, Han Hong, Alessandro Tarozzi
Semiparametric Efficiency In Gmm Models Of Nonclassical Measurement Errors, Missing Data And Treatment Effects, Xiaohong Chen, Han Hong, Alessandro Tarozzi
Cowles Foundation Discussion Papers
We study semiparametric efficiency bounds and efficient estimation of parameters defined through general nonlinear, possibly non-smooth and over-identified moment restrictions, where the sampling information consists of a primary sample and an auxiliary sample. The variables of interest in the moment conditions are not directly observable in the primary data set, but the primary data set contains proxy variables which are correlated with the variables of interest. The auxiliary data set contains information about the conditional distribution of the variables of interest given the proxy variables. Identification is achieved by the assumption that this conditional distribution is the same in both …