[1] "Self-Normalized KPSS Tests with Power Enhancement" (with Xiaojun Song), Journal of Time Series Analysis, January 2025. Main Paper

Self-normalized Tests for Skewness, Kurtosis, and Normality for Time Series Data. (With Xiaojun Song)

Testing for skewness, kurtosis, and normality for time series data is highly relevant for modeling and testing purposes in econometrics. It also affects our understanding of many economic and financial phenomena and the validity of the models developed to explain them. In this paper, we propose self-normalized tests for skewness, kurtosis, and normality that can eliminate the effect of the long-run variance. In particular, our tests allow us to avoid using the long-run variance estimator, which is poorly approximated in finite samples. Consequently, our tests rule out the need to choose the lag-truncation parameter. We present general conditions on the self-normalization function and give two simple examples using the fixed-b asymptotics and the simple normalization proposed by Lobato (2001). Monte Carlo simulations show that the self-normalized tests for skewness and normality have good finite-sample size and power properties, while the test for kurtosis presents substantial size distortions unless the distribution has thin tails like the normal distribution. Finally, we apply the tests to 18 macroeconomic and financial series to study their symmetry, kurtosis, and normality.

Threshold Cointegration Model with Non-stationary Threshold Variable. (With Xiaojun Song)

In this study, we analyze the presence of multiple cointegration relations through a threshold framework where the non-linear relationship arises from introducing state-dependent behavior in the long-run equilibrium relationship, driven by the non-stationary regressor variable. Detecting these types of relationships requires both, the presence of cointegration and a threshold effect. To do so, we propose an extension of the KPSS test to detect cointegration that accounts for the presence of a threshold effect, and provide a SupWald-type test to detect the threshold effect. As an empirical illustration, we extend the intrinsic asset price bubble model introduced by Froot and Obstfeld [1991] by allowing the bubble component to be driven by dividends, thereby capturing periods when the bubble expands and when it implodes. We use the threshold cointegration model to test both, the presence of a cointegration relation between price and dividend, as well as testing for the presence of intrinsic bubbles in the U.S stock price.

Threshold Stochastic Unit Root Models.

In this study, we introduce a new class of stochastic unit-root (STUR) processes, where a threshold variable drives the randomness of the autoregressive unit root, thereby allowing us to explain the existence of unit roots. This new model, namely the threshold autoregressive stochastic unit root (TARSUR) process, is strictly stationary, but if we do not consider the threshold effect, it can mislead to conclude that the process has a unit root. The TARSUR models are not only an alternative to fixed unit root models but present interpretation, estimation and testing advantages with respect to the existent STUR models. This study analyzes the properties of the TARSUR models and proposes two simple tests to identify this type of processes. The first test will allow us to detect the presence of unit roots, which can be fixed or stochastic, and the asymptotic distribution (AD) of this test presents a distribution discontinuity depending if the unit root is fixed or stochastic. The second test we propose is a simple t-statistic (or the supremum of a sequence of t-statistics) for testing the null hypothesis of a fixed unit root versus a stochastic unit root hypothesis. It is shown that its asymptotic distribution (AD) depends if the threshold value is identified under the null hypothesis or not. When the threshold parameter is known, the AD is a standard normal distribution, while in the case of an unknown threshold value, the AD is a functional of Brownian Bridge. A Monte Carlo simulation shows that the proposed tests behave very well in finite sample, and the Dickey-Fuller test cannot easily distinguish between exact unit roots and threshold stochastic unit roots. The study concludes with applications to U.S. stock prices, U.S. house prices, U.S. interest rates, and USD/Pound exchange rates.

Multiple Long Run Equilibria Through Cointegration Eyes.

Cointegration has succeeded in capturing the unique long-run linear equilibrium. Specific non-linearities have been incorporated into cointegrated models but always assuming the existence of a single equilibrium. In this study, we explore the possibility of different long-run equilibria depending on the state of the world (i.e., good and bad times, optimism and pessimism, frictional coordination) in a threshold framework. Starting from the present-value model (PVM) with different discount factors and depending on the state of the economy, we show that this type of PVM implies threshold cointegrated with different long-run equilibria. We present the estimation and inference theory. The study completes two applications where the variables are not linearly cointegrated but threshold cointegrated.

Unveiling Lies in Disguise: A Test of Lying Aversion Theories. (With Jin-yeong Sohn, and Xu Cheng)

We provide an experimental test to distinguish two prominent theories of lying aversion: perceived cheating aversion (Dufwenberg & Dufwenberg 2018) and reputation for honesty (Gneezy et al. 2018, Khalmetski & Sliwka 2019). We use a novel belief-elicitation method, which allows us to estimate the subjects’ strategies, i.e. probability of reporting y ∈ {1, · · · , 6} conditional on die roll x ∈ {1, · · · , 6}. We also compare lying behavior across various non-linear payoff schemes. Our results support no-downward-lies and uniform-cheating properties proposed by Dufwenberg & Dufwenberg (2018). We find partial support for an implication of reputation for honesty; people use maximal lies more (less) frequently under a convex (concave) payoff scheme.

Private Card-shredding Game: A Trade-off between Truth and Lies. (With Jin-yeong Sohn)

Fischbacher & Föllmi-Heusi’s (2013) die-roll paradigm provides an experimental method of measuring cheating behavior by comparing report distributions to the uniform distribution. We point out that, given the sample sizes commonly used in the literature, this method may lead to erroneous inferences about lying behavior. To address this issue, we provide an alternative design called private card-shredding game. We conduct an experiment using this alternative design and find that there is a tradeoff between the experimenters’ access to truths and lies; if they are to observe lies, they must give up on knowing the empirical distribution of private signals.

A Multiple Testing Problem Under the Die-roll Paradigm (With Jin-yeong Sohn)

We explore a potential multiple testing problem under the die-roll paradigm (Fischbacher & Föllmi-Heusi’s 2013). We propose a remedy that can mitigate this problem. We perform a power analysis of the common statistical inferences of lying patterns, which may guide sample size selection in future experiments.

• You can find the supplementary web in https://expeconapp.com/ and the permanent repository in https://github.com/junjipeng/Experimental_Economics_web_apps
• R&R in the Journal of the Economic Science Association.

Obvious Monotonicity: Separating Risk Preferences from Complexity-Induced Mistakes (With Jin-yeong Sohn)

(Circulated before as "Obvious Monotonicity as a Test of Behavioral Incentive Compatibility.")

Preference elicitation mechanisms are often too complex, leading subjects to make “mistakes”. Such complexity-induced mistakes challenge the revealed preference paradigm. We propose a simple behavioral condition, obvious monotonicity, that tests whether a subject’s behavior should be interpreted as an expression of preferences, and when it should be attributed to uninformative mistakes. We apply this to Oprea’s (2024a) “mirror” experiment, which leads to the results that challenge the behavioral foundations of risk preferences. We find that the elicitation tasks fail to induce behavior that are preference-relevant. First, a large proportion of subjects fails OM: e.g., a half of subjects value 90 boxes with $25 less than 10 boxes with $25. Second, the mirror anomalies are mainly driven by random choices of OM violators. Third, among those satisfying OM, we found the fourfold pattern and loss aversion that cannot be attributed to complexity.

Rationalizing Flat-Rate Pricing. (With Jin-yeong Sohn. We wrote this paper during the pandemic and completly forgot about it)

Flat-rate, or buffet pricing—charging a fixed price for unlimited quantity—has gained popularity in various markets, from restaurants and telecommunication to online streaming services. We study a model of buffet pricing, explore applications, and investigate whether and under what market conditions such a pricing scheme is preferred to the common linear pricing. Buffet pricing is more profitable if consumers are sufficiently homogeneous in satiation quantity, or consumers have similar satiation utilities (and low marginal cost). Linear pricing may outperform buffet pricing when consumers are heterogeneous in satiation quantity, marginal cost is high, or consumers have large satiation quantities. Furthermore, under competition, linear pricing outperforms buffet pricing.

Dogbei University of Finance and Economics

• Ph.D. level, Topics in Econometrics (2023-present)

• Ph.D. level, Econometric II (2023-present)

• Ph.D. level, Statistic Summer Course (2021-2022)

Universidad Carlos III de Madrid, 2014-2019

• Teacher Assistant, Ph.D. level. Econometric III (2016-2019)

• Teacher Assistant, Master level. Econometric II (2015-2019)

• Teacher Assistant, Undergraduate level. Econometric Thechiques (2014-2019)

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