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2018

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Institution
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Articles 1 - 30 of 91

Full-Text Articles in Econometrics

Money Is More Than Memory, Maria Bigoni, Gabriele Camera, Marco Casari Dec 2018

Money Is More Than Memory, Maria Bigoni, Gabriele Camera, Marco Casari

ESI Working Papers

Impersonal exchange is the hallmark of an advanced society and money is one key institution that supports it. Economic theory regards money as a crude arrangement for monitoring counterparts’ past conduct. If so, then a public record of past actions—or memory—should supersede the function performed by money. This intriguing theoretical postulate remains untested. In an experiment, we show that the suggested functional equivalence between money and memory does not translate into an empirical equivalence: money removed the incentives to free ride, while memory did not. Monetary systems performed a richer set of functions than just revealing past behaviors.

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Modeling Interactions Between Risk, Time, And Social Preferences, Mark Schneider Dec 2018

Modeling Interactions Between Risk, Time, And Social Preferences, Mark Schneider

ESI Working Papers

Recent studies have observed systematic interactions between risk, time, and social preferences that constitute violations of `dimensional independence' and are not explained by the leading models of decision making. This note provides a simple approach to modeling such interaction effects while predicting new ones. In particular, we present a model of rational-behavioral preferences that takes the convex combination of `behavioral' System 1 preferences and `rational' System 2 preferences. The model provides a unifying approach to analyzing risk, time, and social preferences, and predicts how these preferences are correlated with reliance on System 1 or System 2 thinking.

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A Dual System Model Of Risk And Time Preferences, Mark Schneider Dec 2018

A Dual System Model Of Risk And Time Preferences, Mark Schneider

ESI Working Papers

Discounted Expected Utility theory has been a workhorse in economic analysis for over half a century. However, it cannot explain empirical violations of 'dimensional independence' demonstrating that risk interacts with time preference and time interacts with risk preference, nor does it explain present bias or magnitude-dependence in risk and time preferences, or correlations between risk preference, time preference, and cognitive reflection. We demonstrate that these and other anomalies are explained by a dual system model of risk and time preferences that unless models of a rational economic agent, models based on prospect theory, and dual process models of decision making.

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The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Heidi Margaret Artigue Dec 2018

The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Heidi Margaret Artigue

Pomona Faculty Publications and Research

Principal components regression (PCR) reduces a large number of explanatory variables down to a small number of principal components. PCR is thought to be more useful, the more numerous the potential explanatory variables. The reality is that a large number of candidate explanatory variables does not make PCR more valuable; instead, it magnifies the failings of PCR.

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Using Response Times To Measure Ability On A Cognitive Task, Aleksandr Alekseev Dec 2018

Using Response Times To Measure Ability On A Cognitive Task, Aleksandr Alekseev

ESI Working Papers

I show how using response times as a proxy for effort coupled with an explicit process-based model can address a long-standing issue of how to separate the effect of cognitive ability on performance from the effect of motivation. My method is based on a dynamic stochastic model of optimal effort choice in which ability and motivation are the structural parameters. I show how to estimate these parameters from the data on outcomes and response times in a cognitive task. In a laboratory experiment, I find that performance on a Digit-Symbol test is a noisy and biased measure of cognitive ability. …

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Rhode Island Current Conditions Index -- December 2018, Leonard Lardaro Dec 2018

Rhode Island Current Conditions Index -- December 2018, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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Semiparametric Maximum Likelihood Inference For Nonignorable Nonresponse With Callbacks, Zhong Guan, Denis H. Y. Leung, Jing Qin Dec 2018

Semiparametric Maximum Likelihood Inference For Nonignorable Nonresponse With Callbacks, Zhong Guan, Denis H. Y. Leung, Jing Qin

Research Collection School Of Economics

We model the nonresponse probabilities as logistic functions ofthe outcome variable and other covariates in the survey sampling study withcallback. The identification aspect of this callback model is investigated. Semiparametricmaximum likelihood estimators of the parameters in the responseprobabilities are proposed and studied. As a result, an efficient estimator ofthe mean of the outcome variable is constructed using the estimated responseprobabilities. Moreover, if a regression model for conditional mean of the outcomevariable given some covariate is available, then we can obtain an evenmore efficient estimate of the mean of the outcome variable by fitting the regressionmodel using an adjusted least squares …

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Root-N Consistency Of Intercept Estimators In A Binary Response Model Under Tail Restrictions, Lili Tan, Yichong Zhang Dec 2018

Root-N Consistency Of Intercept Estimators In A Binary Response Model Under Tail Restrictions, Lili Tan, Yichong Zhang

Research Collection School Of Economics

The intercept of the binary response model is irregularly identified when the supports of both the special regressor V and the error term ε are the whole real line. This leads to the estimator of the intercept having potentially a slower than √n convergence rate, which can result in a large estimation error in practice. This paper imposes addition tail restrictions which guarantee the regular identification of the intercept and thus the √n-consistency of its estimator. We then propose an estimator that achieves the √n rate. Finally, we extend our tail restrictions to a full-blown model with endogenous regressors.

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Mild-Explosive And Local-To-Mild-Explosive Autoregressions With Serially Correlated Errors, Yiu Lim Lui, Weilin Xiao, Jun Yu Dec 2018

Mild-Explosive And Local-To-Mild-Explosive Autoregressions With Serially Correlated Errors, Yiu Lim Lui, Weilin Xiao, Jun Yu

Research Collection School Of Economics

This paper firstly extends the results of Phillips and Magdalinos (2007a) by allowing for anti-persistent errors in mildly explosive autoregressive models. It is shown that the Cauchy asymptotic theory remains valid for the least squares (LS) estimator. The paper then extends the results of Phillips, Magdalinos and Giraitis (2010) by allowing for serially correlated errors of various forms in local-to-mild-explosive autoregressive models. It is shown that the result of smooth transition in the limit theory between local-to-unity and mild-explosiveness remains valid for the LS estimator. Finally, the limit theory for autoregression with intercept is developed.

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Forecasting Large Covariance Matrix With High-Frequency Data: A Factor Correlation Matrix Approach, Yingjie Dong, Yiu Kuen Tse Dec 2018

Forecasting Large Covariance Matrix With High-Frequency Data: A Factor Correlation Matrix Approach, Yingjie Dong, Yiu Kuen Tse

Research Collection School Of Economics

We propose a factor correlation matrix approach to forecast large covariance matrix of asset returns using high-frequency data. We apply shrinkage method to estimate large correlation matrix and adopt principal component method to model the underlying latent factors. A vector autoregressive model is used to forecast the latent factors and hence the large correlation matrix. The realized variances are separately forecasted using the Heterogeneous Autoregressive model. The forecasted variances and correlations are then combined to forecast large covariance matrix. We conduct Monte Carlo studies to compare the finite sample performance of several methods of forecasting large covariance matrix. Our proposed …

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Quantile Treatment Effects And Bootstrap Inference Under Covariate-Adaptive Randomization, Xin Zheng, Yichong Zhang Dec 2018

Quantile Treatment Effects And Bootstrap Inference Under Covariate-Adaptive Randomization, Xin Zheng, Yichong Zhang

Research Collection School Of Economics

This paper studies the estimation and inference of the quantile treatment effect under covariate-adaptive randomization. We propose three estimation methods: (1) the simple quantile regression (QR), (2) the QR with strata fixed effects, and (3) the inverse propensity score weighted QR. For the three estimators, we derive their asymptotic distributions uniformly over a set of quantile indexes and show that the estimator obtained from inverse propensity score weighted QR weakly dominates the other two in terms of efficiency, for a wide range of randomization schemes. For inference, we show that the weighted bootstrap tends to be conservative for methods (1) …

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On Booms That Never Bust: Ambiguity In Experimental Asset Markets With Bubbles, Brice Corgnet, Roberto Hernán-González, Praveen Kujal Nov 2018

On Booms That Never Bust: Ambiguity In Experimental Asset Markets With Bubbles, Brice Corgnet, Roberto Hernán-González, Praveen Kujal

ESI Working Papers

We study the effect of ambiguity on the formation of bubbles and on the occurrence of crashes in experimental asset markets à la Smith, Suchanek, and Williams (1988). We extend their framework to an environment where the fundamental value of the asset is ambiguous. We show that, when the fundamental value is ambiguous, asset prices tend to be lower than when it is risky although bubbles form in both the ambiguous and the risky environments. Additionally, bubbles do not crash in the ambiguous case whereas they do so in the risky one. These findings regarding depressed prices and the absence …

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Conditional Independence In A Binary Choice Experiment, Nathaniel Wilcox Nov 2018

Conditional Independence In A Binary Choice Experiment, Nathaniel Wilcox

ESI Working Papers

Experimental and behavioral economists, as well as psychologists, commonly assume conditional independence of choices when constructing likelihood functions for structural estimation. I test this assumption using data from a new experiment designed for this purpose. Within the limits of the experiment’s identifying restriction and designed power to detect deviations from conditional independence, conditional independence is not rejected. In naturally occurring data, concerns about violations of conditional independence are certainly proper and well-taken (for well-known reasons). However, when an experimenter employs contemporary state-of-the-art experimental mechanisms and designs, the current evidence suggests that conditional independence is an acceptable assumption for analyzing data …

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Selection In The Lab: A Network Approach, Aleksandr Alekseev, Mikhail Freer Nov 2018

Selection In The Lab: A Network Approach, Aleksandr Alekseev, Mikhail Freer

ESI Working Papers

We study the selection problem in economic experiments by focusing on its dynamic and network aspects. We develop a dynamic network model of student participation in a subject pool, which assumes that students' participation is driven by the two channels: the direct channel of recruitment and the indirect channel of student interaction. Using rich recruitment data from a large public university, we find that the patterns of participation and biases are consistent with the model. We also find evidence of both short- and long-run selection biases between males and females, as well as between cohorts of students. Males tend to …

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The Grid Bootstrap For Continuous Time Models, Yiu Lim Lui, Weilin Xiao, Jun Yu Nov 2018

The Grid Bootstrap For Continuous Time Models, Yiu Lim Lui, Weilin Xiao, Jun Yu

Research Collection School Of Economics

This paper considers the grid bootstrap for constructing confidence intervals for the persistence parameter in a class of continuous time models driven by a Levy process. Its asymptotic validity is established by assuming the sampling interval (h) shrinks to zero. Its improvement over the in-fill asymptotic theory is achieved by expanding the coefficient-based statistic around its in fill asymptotic distribution which is non-pivotal and depends on the initial condition. Monte Carlo studies show that the gird bootstrap method performs better than the in-fill asymptotic theory and much better than the long-span theory. Empirical applications to U.S. interest rate data highlight …

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Threshold Regression Asymptotics: From The Compound Poisson Process To Two-Sided Brownian Motion, Ping Yu, Peter C. B. Phillips Nov 2018

Threshold Regression Asymptotics: From The Compound Poisson Process To Two-Sided Brownian Motion, Ping Yu, Peter C. B. Phillips

Research Collection School Of Economics

The asymptotic distribution of the least squares estimator in threshold regression is expressed in terms of a compound Poisson process when the threshold effect is fixed and as a functional of two-sided Brownian motion when the threshold effect shrinks to zero. This paper explains the relationship between this dual limit theory by showing how the asymptotic forms are linked in terms of joint and sequential limits. In one case, joint asymptotics apply when both the sample size diverges and the threshold effect shrinks to zero, whereas sequential asymptotics operate in the other case in which the sample size diverges first …

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Change Detection And The Causal Impact Of The Yield Curve, Shuping Shi, Peter C. B. Phillips, Stan Hurn Nov 2018

Change Detection And The Causal Impact Of The Yield Curve, Shuping Shi, Peter C. B. Phillips, Stan Hurn

Research Collection School Of Economics

Causal relationships in econometrics are typically based on the concept of predictability and are established by testing Granger causality. Such relationships are susceptible to change, especially during times of financial turbulence, making the real-time detection of instability an important practical issue. This article develops a test for detecting changes in causal relationships based on a recursive evolving window, which is analogous to a procedure used in recent work on financial bubble detection. The limiting distribution of the test takes a simple form under the null hypothesis and is easy to implement in conditions of homoskedasticity and conditional heteroskedasticity of an …

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Specification Tests Based On Mcmc Output, Yong Li, Jun Yu, Tao Zeng Nov 2018

Specification Tests Based On Mcmc Output, Yong Li, Jun Yu, Tao Zeng

Research Collection School Of Economics

Two test statistics are proposed to determine model specification after a model is estimated by an MCMC method. The first test is the MCMC version of IOSA test and its asymptotic null distribution is normal. The second test is motivated from the power enhancement technique of Fan et al. (2015). It combines a component (J1) that tests a null point hypothesis in an expanded model and a power enhancement component (J0) obtained from the first test. It is shown that J0 converges to zero when the null model is correctly specified and diverges when the null model is misspecified. Also …

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Estimation Of Large Dimensional Factor Models With An Unknown Number Of Breaks, Shujie Ma, Liangjun Su Nov 2018

Estimation Of Large Dimensional Factor Models With An Unknown Number Of Breaks, Shujie Ma, Liangjun Su

Research Collection School Of Economics

In this paper we study the estimation of a large dimensional factor model when the factor loadingsexhibit an unknown number of changes over time. We propose a novel three-step procedure to detect the breaks if any and then identify their locations. In the first step, we divide the whole time span into subintervals and fit a conventional factor model on each interval. In the second step, we apply the adaptive fused group Lasso to identify intervals containing a break. In the third step, we devise a grid search method to estimate the location of the break on each identified interval. …

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Rhode Island Current Conditions Index -- November 2018, Leonard Lardaro Nov 2018

Rhode Island Current Conditions Index -- November 2018, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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News Co-Occurrence, Attention Spillover, And Return Predictability, Li Guo, Lin Peng, Yubo Tao, Jun Tu Nov 2018

News Co-Occurrence, Attention Spillover, And Return Predictability, Li Guo, Lin Peng, Yubo Tao, Jun Tu

Research Collection School Of Economics

We examine the effect of investor attention spillover on stock return predictability. Using a novel measure, the News Network Triggered Attention index (NNTA), we find that NNTA negatively predicts market returns with a monthly in(out)-of-sample R-square of 5.97% (5.80%). In the cross-section, a long-short portfolio based on news co-occurrence generates a significant monthly alpha of 68 basis points. The results are robust to the inclusion of alternative attention proxies, sentiment measures, other news- and information-based predictors, across recession and expansion periods. We further validate the attention spillover effect by showing that news co-mentioning leads to greater increases in Google and …

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Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su Nov 2018

Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su

Research Collection School Of Economics

We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips’ (2016) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the stationary regressors to diverge with the sample size. We show that we can identify the individuals’ group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties of both the C-Lasso …

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Agglomeration And The Extent Of The Market: An Experimental Investigation Into Spatially Coordinated Exchange, Jordan Adamson Oct 2018

Agglomeration And The Extent Of The Market: An Experimental Investigation Into Spatially Coordinated Exchange, Jordan Adamson

ESI Working Papers

How and why do agglomerations emerge? While economic historians emphasize trade and economic geographers emphasize variety, we still don’t understand the role of coordination. I fill this gap by extending the model of Fudenberg and Ellison (2003) to formalize Smith’s (1776) theory of agglomeration. I then test the model in a laboratory experiment and find individuals tend to coalesce purely to coordinate exchange, with more agglomeration when there is a larger variety of goods in the economy. I also find that tying individuals to the land reduces agglomeration, but magnifies the effect of variety.

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The Supply Side Determinants Of Territory And Conflict, Jordan Adamson, Erik O. Kimbrough Oct 2018

The Supply Side Determinants Of Territory And Conflict, Jordan Adamson, Erik O. Kimbrough

ESI Working Papers

What determines the geographic extent of territory? We microfound and extend Boulding’s “Loss of Strength Gradient” to predict the extensive and intensive margins of conflict across space. We show how economies of scale in the production of violence and varying costs of projecting violence at a distance combine to affect the geographic distribution of conflict and territory. We test and probe the boundaries of this model in an experiment varying the fixed costs of conflict entry. As predicted, higher fixed costs increase the probability of exclusive territories; median behavior closely tracks equilibrium predictions in all treatments.

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Experimental Research On Contests, Roman M. Sheremeta Oct 2018

Experimental Research On Contests, Roman M. Sheremeta

ESI Working Papers

Costly competitions between economic agents are modeled as contests. Researchers use laboratory experiments to study contests and test comparative static predictions of contest theory. Commonly, researchers find that participants’ efforts are significantly higher than predicted by the standard Nash equilibrium. Despite overbidding, most comparative static predictions, such as the incentive effect, the size effect, the discouragement effect and others are supported in the laboratory. In addition, experimental studies examine various contest structures, including dynamic contests (such as multi-stage races, wars of attrition, tug-of-wars), multi-dimensional contests (such as Colonel Blotto games), and contests between groups. This article provides a short review …

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Nonlinearities In The Real Exchange Rates: New Evidence From Developed And Developing Countries, Yamin S. Ahmad, Ming Chien Lo, Olena M. Staveley-O'Carroll Oct 2018

Nonlinearities In The Real Exchange Rates: New Evidence From Developed And Developing Countries, Yamin S. Ahmad, Ming Chien Lo, Olena M. Staveley-O'Carroll

Economics Department Working Papers

This paper investigates nonlinearities in the dynamics of real exchange rates. We use Monte Carlo simulations to establish the size properties of the Teräsvirta-Anderson (1992) and the Teräsvirta (1994) test, when the dynamics of the real exchange rate is influenced by an exogenous process. In addition, we examine the modification proposed by Ahmad, Lo and Mykhaylova (2013; Journal of International Economics) to show that the modified nonlinearity test performs much better than the original in both Monte Carlo exercises and in the actual data on 1431 bilateral real exchange rate series. Finally, we investigate the dynamics of the real exchange …

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Preferences (Partial Pre-Orders) On Complex Numbers -- In View Of Possible Use In Quantum Econometrics, Songsak Sriboonchitta, Vladik Kreinovich, Olga Kosheleva Oct 2018

Preferences (Partial Pre-Orders) On Complex Numbers -- In View Of Possible Use In Quantum Econometrics, Songsak Sriboonchitta, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

In economic application, it is desirable to find an optimal solution -- i.e., a solution which is preferable to any other possible solution. Traditionally, the state of an economic system has been described by real-valued quantities such as profit, unemployment level, etc. For such quantities, preferences correspond to natural order between real numbers: all things being equal, the more profit the better, and the smaller unemployment, the better. Lately, it turned out that to adequately describe economic phenomena, it is often convenient to use complex numbers. From this viewpoint, a natural question is: what are possible orders on complex numbers? …

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Volume, Volatility, And Public News Announcements, Tim Bollerslev, Jia Li, Yuan Xue Oct 2018

Volume, Volatility, And Public News Announcements, Tim Bollerslev, Jia Li, Yuan Xue

Research Collection School Of Economics

We provide new empirical evidence for the way in which financial markets process information. Our results rely critically on high-frequency intraday price and volume data for the S&P 500 equity portfolio and U.S. Treasury bonds, along with new econometric techniques, for making inference on the relationship between trading intensity and spot volatility around public news announcements. Consistent with the predictions derived from a theoretical model in which investors agree to disagree, our estimates for the intraday volume-volatility elasticity around important news announcements are systematically below unity. Our elasticity estimates also decrease significantly with measures of disagreements in beliefs, economic uncertainty, …

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Rhode Island Current Conditions Index -- October 2018, Leonard Lardaro Oct 2018

Rhode Island Current Conditions Index -- October 2018, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

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Identifying Latent Grouped Patterns In Panel Data Models With Interactive Fixed Effects, Liangjun Su, Gaosheng Ju Oct 2018

Identifying Latent Grouped Patterns In Panel Data Models With Interactive Fixed Effects, Liangjun Su, Gaosheng Ju

Research Collection School Of Economics

We consider the estimation of latent grouped patterns in dynamic panel data models with interactive fixed effects. We assume that the individual slope coefficients are homogeneous within a group and heterogeneous across groups but each individual’s group membership is unknown to the researcher. We consider penalized principal component (PPC) estimation by extending the penalized-profile-likelihood-based C-Lasso of Su, Shi, and Phillips (2016) to panel data models with cross section dependence. Given the correct number of groups, we show that the C-Lasso can achieve simultaneous classification and estimation in a single step and exhibit the desirable property of uniform classification consistency. The …

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