Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Experimentation (5)
- Learning (5)
- Agency (4)
- Dynamic agency (4)
- Repeated principal-agent problem (4)
-
- Bankruptcy penalty (3)
- Dynamic game (3)
- Experimental gaming (3)
- Fiat money (3)
- Financial institutions (3)
- Multiple equilibria (3)
- Rationalizability (3)
- Unit root (3)
- Value of information (3)
- Venture Capital (3)
- Asymptotic leptokurtosis (2)
- Climate change (2)
- Collateral (2)
- Complete information (2)
- Crisis (2)
- Cycle (2)
- Implementation (2)
- Inflation (2)
- Integrated process (2)
- Kernel regression (2)
- Least absolute deviations (2)
- Leverage (2)
- Location shift (2)
- Maskin monotonicity (2)
- Misspecification (2)
Articles 61 - 68 of 68
Full-Text Articles in Social and Behavioral Sciences
Understanding Inflation-Indexed Bond Markets, John Y. Campbell, Robert J. Shiller, Luis M. Viceira
Understanding Inflation-Indexed Bond Markets, John Y. Campbell, Robert J. Shiller, Luis M. Viceira
Cowles Foundation Discussion Papers
This paper explores the history of inflation-indexed bond markets in the US and the UK. It documents a massive decline in long-term real interest rates from the 1990’s until 2008, followed by a sudden spike in these rates during the financial crisis of 2008. Breakeven inflation rates, calculated from inflation-indexed and nominal government bond yields, stabilized until the fall of 2008, when they showed dramatic declines. The paper asks to what extent short-term real interest rates, bond risks, and liquidity explain the trends before 2008 and the unusual developments in the fall of 2008. Low inflation-indexed yields and high short-term …
Asymptotic Theory For Zero Energy Density Estimation With Nonparametric Regression Applications, Qiying Wang, Peter C.B. Phillips
Asymptotic Theory For Zero Energy Density Estimation With Nonparametric Regression Applications, Qiying Wang, Peter C.B. Phillips
Cowles Foundation Discussion Papers
A local limit theorem is given for the sample mean of a zero energy function of a nonstationary time series involving twin numerical sequences that pass to infinity. The result is applicable in certain nonparametric kernel density estimation and regression problems where the relevant quantities are functions of both sample size and bandwidth. An interesting outcome of the theory in nonparametric regression is that the linear term is eliminated from the asymptotic bias. In consequence and in contrast to the stationary case, the Nadaraya-Watson estimator has the same limit distribution (to the second order including bias) as the local linear …
Mean And Autocovariance Function Estimation Near The Boundary Of Stationarity, Liudas Giraitis, Peter C.B. Phillips
Mean And Autocovariance Function Estimation Near The Boundary Of Stationarity, Liudas Giraitis, Peter C.B. Phillips
Cowles Foundation Discussion Papers
We analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. The concept of stationarity is refined, allowing for sample size dependence in the array and paying special attention to the rate at which the boundary unit root case is approached using a localizing coefficient around unity. The primary focus of the present paper is on estimation of the mean, autocovariance and autocorrelation functions within the broad region of stationarity that includes near boundary cases which vary with the sample size. The rate of consistency and the validity of the normal asymptotic approximation …
The Perils Of The Learning Model For Modeling Endogenous Technological Change, William D. Nordhaus
The Perils Of The Learning Model For Modeling Endogenous Technological Change, William D. Nordhaus
Cowles Foundation Discussion Papers
Learning or experience curves are widely used to estimate cost functions in manufacturing modeling. They have recently been introduced in policy models of energy and global warming economics to make the process of technological change endogenous. It is not widely appreciated that this is a dangerous modeling strategy. The present note has three points. First, it shows that there is a fundamental statistical identification problem in trying to separate learning from exogenous technological change and that the estimated learning coefficient will generally be biased upwards. Second, we present two empirical tests that illustrate the potential bias in practice and show …
An Analysis Of The Dismal Theorem, William D. Nordhaus
An Analysis Of The Dismal Theorem, William D. Nordhaus
Cowles Foundation Discussion Papers
In a series of papers, Martin Weitzman has proposed a Dismal Theorem. The general idea is that, under limited conditions concerning the structure of uncertainty and preferences, society has an indefinitely large expected loss from high-consequence, low-probability events. Under such conditions, standard economic analysis cannot be applied. The present study is intended to put the Dismal Theorem in context and examine the range of its applicability, with an application to catastrophic climate change. I conclude that Weitzman makes an important point about selection of distributions in the analysis of decision-making under uncertainty. However, the conditions necessary for the Dismal Theorem …
Cointegrating Rank Selection In Models With Time-Varying Variance, Xu Cheng, Peter C.B. Phillips
Cointegrating Rank Selection In Models With Time-Varying Variance, Xu Cheng, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Reduced rank regression (RRR) models with time varying heterogeneity are considered. Standard information criteria for selecting cointegrating rank are shown to be weakly consistent in semiparametric RRR models in which the errors have general nonparametric short memory components and shifting volatility provided the penalty coefficient C n → infinity and C n /n → 0 as n → ∞. The AIC criterion is inconsistent and its limit distribution is given. The results extend those in Cheng and Phillips (2008) and are useful in empirical work where structural breaks or time evolution in the error variances is present. An empirical application …
Bootstrapping I(1) Data, Peter C.B. Phillips
Bootstrapping I(1) Data, Peter C.B. Phillips
Cowles Foundation Discussion Papers
A functional law for an I(1) sample data version of the continuous-path block bootstrap of Paparoditis and Politis (2001) is given. The results provide an alternative demonstration that continuous-path block bootstrap unit root tests are consistent under the null.
Efficient Estimation Of Copula-Based Semiparametric Markov Models, Xiaohong Chen, Wei Biao Wu, Yanping Yi
Efficient Estimation Of Copula-Based Semiparametric Markov Models, Xiaohong Chen, Wei Biao Wu, Yanping Yi
Cowles Foundation Discussion Papers
This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant (one-dimensional marginal) distributions and parametric bivariate copula functions; where the copulas capture temporal dependence and tail dependence of the processes. The Markov processes generated via tail dependent copulas may look highly persistent and are useful for financial and economic applications. We first show that Markov processes generated via Clayton, Gumbel and Student’s t $ copulas and their survival copulas are all geometrically ergodic. We then propose a sieve maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the …