133. June 27, 2019, Thursday
132. May 31, 2019, Friday
131. Friday 24, 2019, Friday
130. May 24, 2019, Friday
129. May 21, 2019, Tuesday
128. May 15, 2019, Wednesday
120--127. May 17, 2019, Friday
119. May 15, 2o19, Wednesday
118. May 16, 2019, Thursday
117. May 9, 2019, Thursday
116. May 7, 2019, Tuesday
115. April 25, 2019, Thursday
114. April 25, 2019, Thursday
113. March 25, 2019, Monday
112. March 21, 2o19, Thursday
111. March 19, 2019, March
110. March 4, 2019, Monday
- Speaker: Prof. Miao, Bin (Shanghai University of Finance and Economics)
- Title: Multiple-Switching Behavior in the Elicitation of Risk Preferences
- Time: 10:30--11:30
- Venue: A208
- Chair: Dr. Sun, Xiang
- Abstract: While it is commonly observed that subjects switch multiple times in the choice list elicitation of risk preference, little has been done to systematically examine the nature of this multiple switching behavior (MSB). We differentiate two types of MSB: for odd (even) MSB, subjects initially choose options on the left hand side, and eventually switch to options on the right (left) hand side. In two experiments, we observe that subjects with higher frequency of odd MSB are more likely to deliberately randomize in repeated choices presented three times in a row (Agranov and Ortoleva, 2017), and to exhibit Allais-type behavior as well as to satisfy reduction of compound lottery axiom at the same time. By contrast, we show that subjects with higher frequency of even MSB are more likely to violate first-order stochastic dominance. Our results support models of deliberate randomization to partially account for MSB, and enable a further discrimination among models of stochastic choice.
132. May 31, 2019, Friday
- Speaker: Dr. Dessi, Roberta (Toulouse School of Economics)
- Title: Shame, Guilt and Self-Confidence: an Economic Analysis
- Time: 10:00--11:30
- Venue: A208
- Chair: Dr. Li, Xiaoxi
- Abstract: The evidence from anthropology, psychology and economics shows that sensitivity to the emotion of shame varies across cultures. So does the tendency to exhibit overconfidence. This paper explores the connection between these two observations. It also sheds light on the, related, role of the sensitivity to guilt. Shame and guilt have been portrayed as alternative mechanisms to enforce cooperation. We focus on a key difference between shame and guilt: shame is less sensitive to an individual’s private information, making it a rather blunt instrument, while guilt is more vulnerable to manipulation by the self (e.g. excuses, selective attention, exploiting moral wiggle room…). Shame and guilt influence individual behaviour in a variety of dimensions, including their effect on individuals’ incentives to pursue long-term goals and invest in new projects. Taking this into account, we investigate how reliance on guilt versus shame interacts with a different psychological incentive mechanism: overconfidence. We investigate our model’s predictions using data on differences in self-confidence and in shame and guilt sensitivity across countries, as well as individual-level data on migrants.
131. Friday 24, 2019, Friday
- Speaker: Dr. Li, Sanxi (Renmin University of China)
- Title: Sharing Consumers’ Data in Vertically Differentiated Duopoly
- Time: 15:00--16:30
- Venue: A208
- Chair: Dr. Han, Lining
- Abstract: This paper investigates the incentives and effects of competing firms sharing consumers’ personal information in a duopoly market, where two firms sell vertically differentiated products. We derive firms’ pricing strategies and welfares of all parties under different information structures. And we show that only when firm with less competitive advantage has all consumers’ information will sell part of consumers’ personal information to its competitor to maximize the total revenue. The smaller the competitive advantage of the firm, the more personal information of consumers will be sold to their competitors. To maximize the profits of the whole industry and also social welfare, all consumers’ personal information should be owned by the firm with competitive advantage.
130. May 24, 2019, Friday
- Speaker: Prof. Zhang, Qunzi (Shandong University)
- Title: World Rare Disaster Concerns and Stock Returns
- Time: 10:00--11:30
- Venue: A208
- Chair: Dr. Lin, Qian
- Abstract: We propose an ex ante rare disaster index relying on the six news implied rare disaster measures of Manela and Moreira (2017). The new index can strongly predict international stock returns (including both developed and emerging markets) in-sample and out-of-sample, and deliver sizable economic value for investors. The predictive power of the index is above and beyond traditional predictors such as the dividend yield and interest rates. This evidence is consistent with economic theories emphasizing globally shared rare disaster risk and time-varying disaster risk as an important driving force of asset price fluctuations.
129. May 21, 2019, Tuesday
- Speaker: Prof. Yang, Zhaojun (Southern University of Science and Technology)
- Title: 基于信息不对称的担保互换和企业融资分析
- Time: 09:00--10:30
- Venue: A208
- Chair: Dr. Lin, Qian
- Abstract: 本文给出担保经济学分析,构建单周期担保定价模型,比较分析担保换费用(FGS)、担保换股权(EGS)和担保换期权(OGS)的融资特点。揭示信息不对称对社会福利影响的经济规律,探索异质企业的融资偏好。结论表明:信息不对称导致高盈利企业受损,低盈利企业或担保公司受益,其影响程度在OGS担保模式下最高,EGS次之,FGS最低;高盈利企业可能被迫将部分利润转移给低盈利企业,当且仅当低盈利企业净投资价值为负时才会产生社会福利损失;高盈利企业可能将部分利润转移给担保公司,迫使低盈利企业放弃投资;随着投资成本提高,高盈利企业净投资价值可能反而逐步增加;给出了高风险企业难以获得担保融资的经济学原因。
128. May 15, 2019, Wednesday
- Speaker: Dr. Chao, Yong (University of Louisville)
- Title: Optimal Nonlinear Pricing by a Dominant Firm under Competition
- Time: 14:00--15:30
- Venue: B127
- Chair: Dr. Cui, Jingbo
- Abstract: We consider the nonlinear pricing problem faced by a dominant firm which competes with a capacity-constrained minor firm for a downstream buyer who may purchase the product from one or both firms under complete information. In particular, we analyze a three-stage game in which the dominant firm offers a general tariff first and then the minor firm responds with a per-unit price, followed by the buyer choosing her purchases from both firms. By establishing an equivalence between the subgame perfect equilibrium of our asymmetric competition game and the optimal mechanism in a “virtual” principal-agent model, we characterize the dominant firm's optimal nonlinear tariff. The optimal tariff exhibits convexity, and meanwhile can display quantity discounts. We thus provide a rationale for nonlinear pricing under competition in the absence of private information: The dominant firm can use unchosen offers to constrain its rival's possible deviations and extract more surplus from the buyer. Antitrust implications of our analysis are also discussed.
120--127. May 17, 2019, Friday
- They are included in Environmental and Resource Economics Workshop
- Venue: A208
- Speaker: Dr. Yu, Haishan (Shanghai Jiaotong University)
- Discussant: Dr. Zhang, Junjie (Duke University/Kushan Duke University)
- Time: 16:45--17:30
- Speaker: Dr. Tang, Qu (Jinan University)
- Discussant: Dr. Li, Xun (Wuhan University)
- Time: 16:00--16:45
- Speaker: Dr. Wang, Min (Peking University)
- Discussant: Dr. Cheng, Lei (Wuhan University)
- Time: 15:00--15:45
- Speaker: Dr. Zhang, Peng (The Hong Kong Polytechnic University)
- Discussant: Dr. Zhu, Yin (Zhongnan University of Economics and Law)
- 14:15--15:00
- Speaker: Dr. Cui, Jingbo (Wuhan University)
- Discussant: Prof. Yin, Haitao (Shanghai Jiaotong University)
- Time: 11:30--12:15
- Speaker: Dr. Gong, Yazhen (Renmin University of China)
- Discussant: Dr. Tang, Qu (Jinan University)
- Time: 10:45--11:30
- Speaker: Prof. Yin, Haitao (Shanghai Jiaotong University)
- Discussant: Dr. Zhang, Peng (The Hong Kong Polytechnic University)
- Time: 09:45--10:30
- Speaker: Prof. Zhang, Bing (Nanjing University)
- Discussant: Dr. Zhang, Junjie (Duke University/Kushan Duke University)
- Time: 09:00--09:45
119. May 15, 2o19, Wednesday
- Speaker: Mr. Liu, Renxiong (The Ohio State University)
- Title: An algorithmic view of L_2 regularization and some path-following Algorithms
- Time: 15:30--17:00
- Venue: B127
- Chair: Dr. Li, Xun
- Abstract: We establish an equivalence between L_2-regularized solution path and the solution of an ordinary differentiable equation (ODE).Importantly, this equivalence reveals that the solution path can be viewed as the flow of a hybrid of gradient descent and Newton method applying to the empirical loss, which is similar to a widely used optimization technique called trust region method. This provides an interesting algorithmic view of L_2 regularization, and is in contrast to the conventional view that the L_2 regularization solution path is similar to the gradient flow of the empirical loss. Interestingly, the limit of the solution path is shown to coincide with the minimum L_2 norm minimizer of the empirical loss provided that it is finite.Path-following algorithms based on homotopy method and numerical ODE solvers are considered to numerically approximate the solution path. In particular, we consider Newton update and gradient descent update as the basis algorithm for the homotopy method, and establish their the global approximation error rates. In terms of computational cost, these path-following algorithms are shown to require roughly thesame computational cost needed for computing a single solution on the path. Finally, we use L_2-regularized logistic regression as an illustrating example to demonstrate the effectiveness of the proposed path-following algorithms.
118. May 16, 2019, Thursday
- Speaker: Dr. Chen, Liang (Shanghai University of Finance and Economics)
- Title: Quantile Factor Models
- Time: 10:00--11:30
- Venue: A204
- Chair: Dr. Chuang, O-Chia
- Abstract: Quantile Factor Models (QFM) represent a new class of factor models for high-dimensional panel data. Unlike Approximate Factor Models (AFM), where only mean-shifting factors can be extracted, QFM also allow to recover unobserved factors shifting other relevant parts of the distributions of observed variables. A quantile regression approach, labeled Quantile Factor Analysis (QFA), is proposed to consistently estimate all the quantile-dependent factors and loadings. Their asymptotic distribution is then derived using a kernel-smoothed version of the QFA estimators. Two consistent model selection criteria, based on information criteria and rank minimization, are developed to determine the number of factors at eachquantile. Moreover, in contrast to the conditions required for the use of Principal Components Analysis in AFM, QFA estimation remains valid even when the idiosyncratic errors have heavy-tailed distributions. Three empirical applications (regarding climate, financial and macroeconomic panel data) provide evidence that extra factors shifting quantiles other than the means could be relevant in practice.
117. May 9, 2019, Thursday
- Speaker: Dr. Zhang, Jun (Nanjing Audit University)
- Title: Fractional Top Trading Cycle
- Time: 14:00--15:30
- Venue: B249
- Chair: Dr. Han, Lining
- Abstract: We generalize the Top Trading Cycle mechanism to solve random assignment problems. Specifically, we study the fractional endowment exchange problem in which each agent may own fractional amounts of multiple objects and each object may be owned by multiple agents. We propose a class of mechanisms based on a linear programming method. At every step, our mechanisms let agents point to most preferred objects and objects point to all of their owners. We use a linear equation system to describe how to trade the network generated at every step. Interestingly, the equation system is an instance of the classical Leontief input-output model so that its solutions must exist. We provide an intuitive explanation of our mechanisms: at every step, there exist disjoint absorbing sets in the generated network and agents in each absorbing set trade endowments only among themselves. All of our mechanisms are individually rational and sd-efficient. We characterize those mechanisms satisfying desirable fairness properties including equal-endowment no envy and stronger notions. We apply the mechanisms to solve real-life problems including school choice with weak priorities and time bank.
116. May 7, 2019, Tuesday
- Speaker: Prof. Wei, K.C. John(The Hong Kong Polytechnic University)
- Title: Speculative Trading, Bitcoin, and Stock Returns
- Time: 10:00--11:30
- Venue: A208
- Chair: Dr. Li, Xiaoxi
- Abstract: We investigate whether the hype surrounding cryptocurrencies spreads into the stock market. Using daily Bitcoin prices from 2013 to 2018, we estimate the absolute sensitivity of individual stock returns to Bitcoin returns. Consistent with speculative trading demand, stocks with high absolute Bitcoin sensitivity experience temporary over-valuation and subsequent return reversals that exceed −1% per month. The return patterns are not due to size, book-to-market, momentum, illiquidity, idiosyncratic volatility, expected idiosyncratic skewness, and maximum daily returns. Additional analysis suggests that retail investors likely drive this speculative demand.
115. April 25, 2019, Thursday
- Speaker: Dr. Chen, Shuai (Zhejiang University)
- Title: The Effect of Air Pollution on Migration: Evidence from China
- Time: 10:30--12:00
- Venue: A208
- Chair: Dr. Cui, Jingbo
- Abstract: This paper looks at the effects of air pollution on migration in China using changes in the average strength of thermal inversions over five-year periods as a source of exogenous variation for medium-run air pollution levels. Our findings suggest that air pollution is responsible for large changes in inflows and outflows of migration in China. Specifically, we find that a 10 percent increase in air pollution, holding everything else constant, is capable of reducing population through net outmigration by about 2.8 percent in a given county. We find that these inflows are primarily driven by well-educated people at the beginning of their professional careers, leading to substantial changes in the sociodemographic composition of the population and labor force of Chinese counties. We also find strong gender asymmetries in the response of mid-age adults that suggests families are splitting across counties to protect vulnerable members of the household. Our results are robust to different specifications, including a spatial lag model that accounts for localized migration spillovers and spatially correlated pollution shocks.
114. April 25, 2019, Thursday
- Speaker: Dr. Liu, Mengdi (Nanjing University)
- Title: Trade Liberalization, Technology Upgrading, and Environmental Outcomes: Evidence from China's Accession to the WTO
- Time: 09:00--10:30
- Venue: A208
- Chair: Dr. Cui, Jingbo
- Abstract: Much concern has been raised over whether trade causes environmental damage in low-income developing countries. In this paper, we estimate the impact of trade liberalization on environmental performance using firm-level data. By adopting Brandt et al (2017)'s approach that uses the tariff rates from the accession agreement as instruments, we find that lowering input tariff leads to higher average SO2 emissions (9-11%) which is largely due to scale effects and composition effects while lowering output tariff has a weak negative effect on SO2 emissions. Given that we have unique and detailed firm-level information, we then trace through in detail the mechanisms through which trade liberalization contributes to technology upgrading. We find that the decrease of import tariff has a net negative effect on SO2 generation intensity which means the extent of free trade increase, the production becomes cleaner. We also find that compared to firms in non-treated cities, firms in cities with a more stringent environmental regulation increase less pollution intensity when the import tariffs decrease, which is consistent with the theory.
113. March 25, 2019, Monday
- Speaker: Dr. Wang, Xiaohu (The Chinese University of Hong Kong)
- Title: Bubble Testing under Deterministic Trends
- Time: 10:00--11:30
- Venue: A221
- Chair: Dr. Liu, Cheng
- Abstract: This paper develops the asymptotic theory of the ordinary least squares estimator of the autoregressive (AR) coefficient in various AR models when data is generated from trend-stationary models in different forms. It is shown that, depending on how the autoregression is specified, the commonly used right-tailed unit root tests may tend to reject the null hypothesis of unit root in favor of the explosive alternative. A new procedure to implement the right-tailed unit root tests is proposed. It is shown that when the data generating process is trend-stationary, the test statistics based on the proposed procedure cannot find evidence of explosiveness. Whereas, when the data generating process is mildly explosive, the unit root tests find evidence of explosiveness. Hence, the proposed procedure enables robust bubble testing under deterministic trends. Empirical implementation of the proposed procedure using data from the stock and the real estate markets in the US reveals some interesting findings. While our proposed procedure flags the same number of bubbles episodes in the stock data as the method developed in Phillips, Shi, and Yu (2015a, PSY), the estimated termination dates by the proposed procedure match better with the data. For real estate data, all negative bubble episodes flagged by PSY are no longer regarded as bubbles by the proposed procedure.
112. March 21, 2o19, Thursday
- Speaker: Dr. Shan, Chenyu (Shanghai University of Finance and Economics)
- Title: The diversification benefits and policy risks of accessing China's stock market
- Time: 14:00--15:30
- Venue: A221
- Chair: Dr. Cui, Jingbo
- Abstract: We find that China’s stock market provides valuable diversification benefits for international investors. It has low correlation with the global market, and is resistant to international financial contagion. These diversification benefits can be explained by the unique features of China’s stock market: frequent government interventions, disconnection with the real economy, and low foreign ownership. The recent Shanghai-Hong Kong and Shenzhen-Hong Kong stock connect programs have minimal impact on these diversification benefits. We further find more trading suspensions but more diversification and better performance for A-share stocks with high policy sensitivity.
111. March 19, 2019, March
- Speaker: Prof. Robinson, Peter M. (London School of Economics and Political Science)
- Title: Long-Range Dependent Curve Time Series
- Time: 15:30--17:00
- Venue: A221
- Chair: Dr. Liu, Cheng
- Abstract: We introduce methods and theory for functional or curve time series with long range dependence. The temporal sum of the curve process is shown to be asymptotically normally distributed, the conditions for this covering a functional version of fractionally integrated autoregressive moving averages. We also construct an estimate of the long-run covariance function, which we use, via functional principal component analysis, in estimating the orthonormal functions spanning the dominant sub-space of the curves. In a semiparametric context, we propose an estimate of the memory parameter and establish its consistency. A Monte-Carlo study of finite sample performance is included, along with two empirical applications. The first of these finds a degree of stability and persistence in intra-day stock returns. The second finds similarity in the extent of long memory in incremental age-specific fertility rates across some developed nations.
110. March 4, 2019, Monday
- Speaker: Arthur Lewbel (Boston College)
- Title: The Identification Zoo---Econometric Identification, Causal and Structural Model Identification
- Time: 09:00--12:00
- Venue: A208
- Chair: Dr. Liu, Cheng
- Abstract: This talk gives a few excerpts from the forthcoming Journal of Economic Literature survey article called, The Identification Zoo---Meanings of Identification in Econometrics. The talk will cover some history of identification, definitions of point identification, and compare identification in structural econometric models to identification in reduced form, causal, and randomization based models.