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Articles 1 - 30 of 759
Full-Text Articles in Social and Behavioral Sciences
Bubbly Booms And Welfare, Feng Dong, Yang Jiao, Haoning Sun
Bubbly Booms And Welfare, Feng Dong, Yang Jiao, Haoning Sun
Research Collection School Of Economics
We show the competing effects of a housing bubble on the real economy by developing a multi-sector dynamic model with housing production. On the one hand, firms can sell or collateralize their housing, so a housing bubble helps firms obtain credit to finance their investment and expand production. On the other hand, a boom in the housing sector crowds out labor in the non-housing sector. We show that housing booms can reduce social welfare both in the steady state and in the transitional dynamics only when the production externalities in the non-housing sector are sufficiently large. We quantitatively evaluate our …
Wild Bootstrap Inference For Instrumental Variables Regressions With Weak And Few Clusters, Wenjie Wang, Yichong Zhang
Wild Bootstrap Inference For Instrumental Variables Regressions With Weak And Few Clusters, Wenjie Wang, Yichong Zhang
Research Collection School Of Economics
We study the wild bootstrap inference for instrumental variable regressions under an alternative asymptotic framework that the number of independent clusters is fixed, the size of each cluster diverges to infinity, and the within cluster dependence is sufficiently weak. We first show that the wild bootstrap Wald test controls size asymptotically up to a small error as long as the parameters of endogenous variables are strongly identified in at least one of the clusters. Second, we establish the conditions for the bootstrap tests to have power against local alternatives. We further develop a wild bootstrap Anderson–Rubin test for the full-vector …
Housing Markets Since Shapley And Scarf, Mustafa Oguz Afacan, Gaoji Hu, Jiangtao Li
Housing Markets Since Shapley And Scarf, Mustafa Oguz Afacan, Gaoji Hu, Jiangtao Li
Research Collection School Of Economics
Shapley and Scarf (1974) appeared in the first issue of the Journal of Mathematical Economics, and is one of the journal’s most impactful publications. As we approach the remarkable milestone of the journal’s 50th anniversary (1974–2024), this article serves as a commemorative exploration of Shapley and Scarf (1974) and the extensive body of literature that follows it.
Optimal Inference For Spot Regressions, Tim Bollerslev, Jia Li, Yuexuan Ren
Optimal Inference For Spot Regressions, Tim Bollerslev, Jia Li, Yuexuan Ren
Research Collection School Of Economics
Betas from return regressions are commonly used to measure systematic financial market risks. "Good" beta measurements are essential for a range of empirical inquiries in finance and macroeconomics. We introduce a novel econometric framework for the nonparametric estimation of time-varying betas with high-frequency data. The "local Gaussian" property of the generic continuous-time benchmark model enables optimal "finite-sample" inference in a well-defined sense. It also affords more reliable inference in empirically realistic settings compared to conventional large-sample approaches. Two applications pertaining to the tracking performance of leveraged ETFs and an intraday event study illustrate the practical usefulness of the new procedures.
Bootstrap Inference For Quantile Treatment Effects In Randomized Experiments With Matched Pairs, Liang Jiang, Xiaobin Liu, Peter C B Phillips, Yichong Zhang
Bootstrap Inference For Quantile Treatment Effects In Randomized Experiments With Matched Pairs, Liang Jiang, Xiaobin Liu, Peter C B Phillips, Yichong Zhang
Research Collection School Of Economics
This paper examines methods of inference concerning quantile treatment effects (QTEs) in randomized experiments with matched-pairs designs (MPDs). Standard multiplier bootstrap inference fails to capture the negative dependence of observations within each pair and is therefore conservative. Analytical inference involves estimating multiple functional quantities that require several tuning parameters. Instead, this paper proposes two bootstrap methods that can consistently approximate the limit distribution of the original QTE estimator and lessen the burden of tuning parameter choice. Most especially, the inverse propensity score weighted multiplier bootstrap can be implemented without knowledge of pair identities.
Robust Inference On Correlation Under General Heterogeneity, Liudas Giraitis, Yuefei Li, Peter C. B. Phillips
Robust Inference On Correlation Under General Heterogeneity, Liudas Giraitis, Yuefei Li, Peter C. B. Phillips
Research Collection School Of Economics
Considerable evidence in past research shows size distortion in standard tests for zero autocorrelation or zero cross-correlation when time series are not independent identically distributed random variables, pointing to the need for more robust procedures. Recent tests for serial correlation and cross-correlation in Dalla, Giraitis, and Phillips (2022) provide a more robust approach, allowing for heteroskedasticity and dependence in uncorrelated data under restrictions that require a smooth, slowly-evolving deterministic heteroskedasticity process. The present work removes those restrictions and validates the robust testing methodology for a wider class of innovations and regression residuals allowing for heteroscedastic uncorrelated and non-stationary data settings. …
Panel Data Models With Time-Varying Latent Group Structures, Yiren Wang, Peter C. B. Phillips, Liangjun Su
Panel Data Models With Time-Varying Latent Group Structures, Yiren Wang, Peter C. B. Phillips, Liangjun Su
Research Collection School Of Economics
This paper considers a linear panel model with interactive fixed effects and unobserved individual and time heterogeneities that are captured by some latent group structures and an unknown structural break, respectively. To enhance realism, the model may have different numbers of groups and/or different group memberships before and after the break. With preliminary nuclear norm regularized estimation followed by row- and column-wise linear regressions, we estimate the break point based on the idea of binary segmentation and the latent group structures together with the number of groups before and after the break by sequential testing K-means algorithm simultaneously. It is …
Equal Predictive Ability Tests Based On Panel Data With Applications To Oecd And Imf Forecasts, Oguzhan Akgun, Alain Pirotte, Giovanni Urga, Zhenlin Yang
Equal Predictive Ability Tests Based On Panel Data With Applications To Oecd And Imf Forecasts, Oguzhan Akgun, Alain Pirotte, Giovanni Urga, Zhenlin Yang
Research Collection School Of Economics
We propose two types of equal predictive ability (EPA) tests with panels to compare the predictions made by two forecasters. The first type, S-statistics, focuses on the overall EPA hypothesis, which states that the EPA holds, on average, over all panel units and over time. The second type, C-statistics, focuses on the clustered EPA hypothesis where the EPA holds jointly for a fixed number of clusters of panel units. The asymptotic properties of the proposed tests are evaluated under weak and strong cross-sectional dependence. An extensive Monte Carlo simulation shows that the proposed tests have very good finite sample properties, …
Optimal Nonparametric Range-Based Volatility Estimation, Tim Bollerslev, Jia Li, Qiyuan Li
Optimal Nonparametric Range-Based Volatility Estimation, Tim Bollerslev, Jia Li, Qiyuan Li
Research Collection School Of Economics
We present a general framework for optimal nonparametric spot volatility estimation based on intraday range data, comprised of the first, highest, lowest, and last price over a given time-interval. We rely on a decision-theoretic approach together with a coupling-type argument to directly tailor the form of the nonparametric estimator to the specific volatility measure of interest and relevant loss function. The resulting new optimal estimators offer substantial efficiency gains compared to existing commonly used range-based procedures.
Robust Testing For Explosive Behavior With Strongly Dependent Errors, Yui Lim Lui, Peter C. B. Phillips, Jun Yu
Robust Testing For Explosive Behavior With Strongly Dependent Errors, Yui Lim Lui, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
A heteroskedasticity-autocorrelation robust (HAR) test statistic is proposed to test for the presence of explosive roots in financial or real asset prices when the equation errors are strongly dependent. Limit theory for the test statistic is developed and extended to heteroskedastic models. The new test has stable size properties unlike conventional test statistics that typically lead to size distortion and inconsistency in the presence of strongly dependent equation errors. The new procedure can be used to consistently time-stamp the origination and termination of an explosive episode under similar conditions of long memory errors. Simulations are conducted to assess the finite …
High-Dimensional Iv Cointegration Estimation And Inference, Peter C. B. Phillips, Igor L. Kheifets
High-Dimensional Iv Cointegration Estimation And Inference, Peter C. B. Phillips, Igor L. Kheifets
Research Collection School Of Economics
A semiparametric triangular systems approach shows how multicointegrating linkages occur naturally in an I(1) cointegrated regression model when the long run error variance matrix in the system is singular. Under such singularity, cointegrated I(1) systems embody a multicointegrated structure that makes them useful in many empirical settings. Earlier work shows that such systems may be analyzed and estimated without appealing to the associated I(2) system but with suboptimal convergence rates and potential asymptotic bias. The present paper develops a robust approach to estimation and inference of such systems using high dimensional IV methods that have appealing asymptotic properties like those …
A Conditional Linear Combination Test With Many Weak Instruments, Dennis Lim, Wenjie Wang, Yichong Zhang
A Conditional Linear Combination Test With Many Weak Instruments, Dennis Lim, Wenjie Wang, Yichong Zhang
Research Collection School Of Economics
We consider a linear combination of jackknife Anderson-Rubin (AR) and orthogonalized Lagrangian multiplier (LM) tests for inference in IV regressions with many weak instruments and heteroskedasticity. We choose the weight in the linear combination based on a decision-theoretic rule that is adaptive to the identification strength. Under both weak and strong identifications, the proposed linear combination test controls asymptotic size and is admissible. Under strong identification, we further show that our linear combination test is the uniformly most powerful test against local alternatives among all tests that are constructed based on the jackknife AR and LM tests only and invariant …
Are Bond Returns Predictable With Real-Time Macro Data?, Dashan Huang, Fuwei Jiang, Kunpeng Li, Guoshi Tong, Guofu Zhou
Are Bond Returns Predictable With Real-Time Macro Data?, Dashan Huang, Fuwei Jiang, Kunpeng Li, Guoshi Tong, Guofu Zhou
Research Collection Lee Kong Chian School Of Business
We investigate the predictability of bond returns using real-time macro variables and consider the possibility of a nonlinear predictive relationship and the presence of weak factors. To address these issues, we propose a scaled sufficient forecasting (sSUFF) method and analyze its asymptotic properties. Using both the existing and the new method, we find empirically that real-time macro variables have significant forecasting power both in-sample and out-of-sample. Moreover, they generate sizable economic values, and their predictability is not spanned by the yield curve. We also observe that the forecasted bond returns are countercyclical, and the magnitude of predictability is stronger during …
Financial Crisis And Female Entrepreneurship: Evidence From South Korea, Jungho Lee, Sunha Myong
Financial Crisis And Female Entrepreneurship: Evidence From South Korea, Jungho Lee, Sunha Myong
Research Collection School Of Economics
We document a drastic increase in female-owned manufacturing firms in South Korea after the 1997 financial crisis. During the crisis, a major banking sector reform was conducted, and many underperforming bank branches were forced to close down. Using a geographical variation of bank branch closures during the reform, we show that the banking sector reform resulted in a rise in female entrepreneurship. We present evidence that male-owned firms were preferred by the closeddown bank branches, despite female-owned firms exhibiting lower risks and higher returns. The banking sector reform, although not explicitly aimed at addressing gender disparities, substantially benefited female entrepreneurs …
Customer Capital And Trade Intermediaries: Evidence From China, Jungho Lee, Jianhuan Xu
Customer Capital And Trade Intermediaries: Evidence From China, Jungho Lee, Jianhuan Xu
Research Collection School Of Economics
Using a unique dataset that links the production and sales of Chinese exporting firms, we document that the value of export goods a firm produces often differs from the value of export goods that the firm sells in foreign markets. We show that this empirical pattern reflects that some exporters act as trade intermediaries, which we refer to as producer intermediaries. We further show that firms with higher accumulated marketing expenditures are more likely to become producer intermediaries. To understand the implications of our empirical findings, we develop a theoretical framework in which firms can lend and borrow customer capital …
Connecting The (Dirty) Dots: Current Account Surplus And Polluting Production, Jungho Lee, Shang-Jin Wei, Jianhuan Xu
Connecting The (Dirty) Dots: Current Account Surplus And Polluting Production, Jungho Lee, Shang-Jin Wei, Jianhuan Xu
Research Collection School Of Economics
According to the existing open-economy macroeconomics literature, a current account surplus is associated with a welfare loss only when distortions exist in either savings or investment. We propose a new welfare effect even in the absence of such distortions. In our theory, a trade imbalance − the largest component of a current account imbalance − interacts with a country’s pollution control (“cleanness”) regime to generate welfare effects outside the standard channels. In particular, a trade surplus alters the shipping costs and composition of a country’s imports, producing a welfare loss associated with greater pollution.
Self-Financing, Parental Transfer, And College Education, Jungho Lee, Sunha Myong
Self-Financing, Parental Transfer, And College Education, Jungho Lee, Sunha Myong
Research Collection School Of Economics
We show that financial constraints can affect the human capital accumulation of college students by influencing students’ labor supply. We document that many college students work a substantial number of hours at low-skill jobs, and students who have fewer financial resources (in particular, parental transfer) tend to work more. We develop a model that incorporates college students’ labor supply and its interaction with parental transfer in the presence of financial constraints. By estimating the model, we quantify the trade-off between self-financing and human capital accumulation and discuss the implications of a wage subsidy policy.
Spatial Disaggregation Of Poverty And Disability: Application To Tanzania, Tomoki Fujii
Spatial Disaggregation Of Poverty And Disability: Application To Tanzania, Tomoki Fujii
Research Collection School Of Economics
Estimating poverty measures for disabled people in developing countries is often difficult, partly because relevant data are not readily available. We extend the small-area estimation developed by Elbers, Lanjouw and Lanjouw (2002, 2003) to estimate poverty by the disability status of the household head, when the disability status is unavailable in the survey. We propose two alternative approaches to this extension: Aggregation and Instrumental Variables Approaches. We apply these approaches to data from Tanzania and show that both approaches work. Our estimation results show that disability is indeed positively associated with poverty in every region of mainland Tanzania.
Common Bubble Detection In Large Dimensional Financial Systems, Ye Chen, Peter C. B. Phillips, Shuping Shi
Common Bubble Detection In Large Dimensional Financial Systems, Ye Chen, Peter C. B. Phillips, Shuping Shi
Research Collection School Of Economics
Price bubbles in multiple assets are sometimes nearly coincident in occurrence. Such near-coincidence is strongly suggestive of co-movement in the associated asset prices and is likely driven by certain factors that are latent in the financial or economic system with common effects across several markets. Can we detect the presence of such common factors at the early stages of their emergence? To answer this question, we build a factor model that includes I(1), mildly explosive, and stationary factors to capture normal, exuberant, and collapsing phases in such phenomena. The I(1) factor models the primary driving force of market fundamentals. The …
The Impact Of Upzoning On Housing Construction In Auckland*, Ryan Greenaway-Mcgrevy, Peter C. B. Phillips
The Impact Of Upzoning On Housing Construction In Auckland*, Ryan Greenaway-Mcgrevy, Peter C. B. Phillips
Research Collection School Of Economics
There is a growing debate about whether upzoning is an effective policy response to housing shortages and unaffordable housing. This paper provides empirical evidence to further inform debate by examining the various impacts of recently implemented zoning reforms on housing construction in Auckland, the largest metropolitan area in New Zealand. In 2016, the city upzoned approximately three quarters of its residential land to facilitate construction of more intensive housing. We use a quasi-experimental approach to analyze the short-run impacts of the reform on construction, allowing for potential shifts in construction from non-upzoned to upzoned areas (displacement effects) that would, if …
Multivariate Stochastic Volatility Models Based On Generalized Fisher Transformation, Han Chen, Yijie Fei, Jun Yu
Multivariate Stochastic Volatility Models Based On Generalized Fisher Transformation, Han Chen, Yijie Fei, Jun Yu
Research Collection School Of Economics
Modeling multivariate stochastic volatility (MSV) can be challenging, particularly when both variances and covariances are time-varying. In this paper, we address these challenges by introducing a new MSV model based on the generalized Fisher transformation of Archakov and Hansen (2021). Our model is highly exible and ensures that the variance-covariance matrix is always positive-definite. Moreover, our approach separates the driving factors of volatilities and correlations. To conduct Bayesian analysis of the model, we use a Particle Gibbs Ancestor Sampling (PGAS) method, which facilitates Bayesian model comparison. We also extend our MSV model to cover the leverage effect in volatilities and …
Uniform Nonparametric Inference For Spatially Dependent Panel Data, Jia Li, Zhipeng Liao, Wenyu Zhou
Uniform Nonparametric Inference For Spatially Dependent Panel Data, Jia Li, Zhipeng Liao, Wenyu Zhou
Research Collection School Of Economics
This article proposes a uniform functional inference method for nonparametric regressions in a panel-data setting that features general unknown forms of spatio-temporal dependence. The method requires a long time span, but does not impose any restriction on the size of the cross section or the strength of spatial correlation. The uniform inference is justified via a new growing-dimensional Gaussian coupling theory for spatio-temporally dependent panels. We apply the method in two empirical settings. One concerns the nonparametric relationship between asset price volatility and trading volume as depicted by the mixture of distribution hypothesis. The other pertains to testing the rationality …
Volatility Puzzle: Long Memory Or Anti-Persistency, Shuping Shi, Jun Yu
Volatility Puzzle: Long Memory Or Anti-Persistency, Shuping Shi, Jun Yu
Research Collection School Of Economics
The log realized volatility (RV) is often modeled as an autoregressive fractionally integrated moving average model ARFIMA(1,d,01,d,0). Two conflicting empirical results have been found in the literature. One stream shows that log RV has a long memory (i.e., the fractional parameter d > 0). The other stream suggests that the autoregressive coefficient α is near unity with antipersistent errors (i.e., d α close to 0 and d close to 0.5) from Model 2Model 2 (ARFIMA(1,d,01,d,0) with α close to unity and d close to –0.5). An intuitive explanation is given. For the 10 financial assets considered, despite that no definitive conclusions …
Disagreement In Market Index Options, Guilherme Salome, George Tauchen, Jia Li
Disagreement In Market Index Options, Guilherme Salome, George Tauchen, Jia Li
Research Collection School Of Economics
We generate new evidence on disagreement among traders in the S&P 500 options market from high-frequency intraday price and volume data. Inference on disagreement is based on a model where investors observe public information but agree to disagree on its interpretation; disagreement among investors is captured by the volume–volatility elasticity. For options, there are two natural variables related to disagreement: moneyness and tenor, which we relate to disagreement about the distribution of the market index at different quantiles and times. The estimated volume–volatility elasticity equals unity for options near the money and close to expiration, which is consistent with the …
Inflation Dynamics And Expectations In Singapore, Hwee Kwan Chow-Tan
Inflation Dynamics And Expectations In Singapore, Hwee Kwan Chow-Tan
Research Collection School Of Economics
Inflation dynamics in Singapore have primarily been shaped by foreign factors, including global inflationary pressures and external macroeconomic shocks. More recently, the normalisation phase of the Covid-19 pandemic crisis has led to domestic price pressures from pent-up demand and supply-chain disruptions. Meanwhile, the war in Ukraine has resulted in a hike in the global prices of food, energy, and industrial commodities. Using inflation forecasts from the MAS Survey of Professional Forecasters as our measure of inflation expectations, we show that short-term inflation expectations have shifted up recently. Moreover, greater disagreement amongst survey respondents in the more recent surveys suggests individual …
Improved Marginal Likelihood Estimation Via Power Posteriors And Importance Sampling, Yong Li, Nianling Wang, Jun Yu
Improved Marginal Likelihood Estimation Via Power Posteriors And Importance Sampling, Yong Li, Nianling Wang, Jun Yu
Research Collection School Of Economics
Power posteriors have become popular in estimating the marginal likelihood of a Bayesian model. A power posterior is referred to as the posterior distribution that is proportional to the likelihood raised to a power b∈[0,1]. Important power-posterior-based algorithms include thermodynamic integration (TI) of Friel and Pettitt (2008) and steppingstone sampling (SS) of Xie et al. (2011). In this paper, it is shown that the Bernstein–von Mises (BvM) theorem holds for power posteriors under regularity conditions. Due to the BvM theorem, power posteriors, when adjusted by the square root of the auxiliary constant, have the same limit distribution as the original …
Economic Forecasting In A Pandemic: Some Evidence From Singapore, Hwee Kwan Chow-Tan, Keen Meng Choy
Economic Forecasting In A Pandemic: Some Evidence From Singapore, Hwee Kwan Chow-Tan, Keen Meng Choy
Research Collection School Of Economics
This paper aims to investigate whether the predictive performance and behaviour of professional forecasters are different during the COVID-19 pandemic as compared with the global financial crisis of 2008 and normal times. To this end, we use a survey of professional forecasters in Singapore collated by the central bank to analyse the forecasting records for GDP growth and CPI inflation for the period 2000Q1–2021Q4. We first examine the point forecasts to document the extent of forecast failure duringthe two crises and explore various explanations for it, such as leader-following and herding behaviour. Then, using percentile-based summary measures of probability distribution …
On The Spectral Density Of Fractional Ornstein-Uhlenbeck Process: Approximation, Estimation, And Model Comparison, Shuping Shi, Jun Yu, Chen Zhang
On The Spectral Density Of Fractional Ornstein-Uhlenbeck Process: Approximation, Estimation, And Model Comparison, Shuping Shi, Jun Yu, Chen Zhang
Research Collection School Of Economics
This paper introduces a novel method for accurately approximating the spectral density of the discretely-sampled fractional Ornstein-Uhlenbeck (fOU) process. We utilize this approximated spec-tral density to develop an estimation method called the approximated Whittle maximum likelihood method (AWML) for fOU. Additionally, we develop a likelihood-ratio (LR) test using the approxi-mated spectral densities to distinguish between the fractional Brownian motion (fBm) and fOU pro-cesses, two popular models in the volatility literature. Simulation studies demonstrate that the AWML method improves the estimation speed and accuracy compared to existing ones and that the LR test is effective in distinguishing between the two processes …
Adjustment With Many Regressors Under Covariate-Adaptive Randomizations, Liang Jiang, Liyao Li, Ke Miao, Yichong Zhang
Adjustment With Many Regressors Under Covariate-Adaptive Randomizations, Liang Jiang, Liyao Li, Ke Miao, Yichong Zhang
Research Collection School Of Economics
Our paper identifies a trade-off when using regression adjustments (RAs) in causal inference under covariate-adaptive randomizations (CARs). On one hand, RAs can improve the efficiency of causal estimators by incorporating information from covariates that are not used in the randomization. On the other hand, RAs can degrade estimation efficiency due to their estimation errors, which are not asymptotically negligible when the number of regressors is of the same order as the sample size. Failure to account for the cost of RAs can result in over-rejection of causal inference under the null hypothesis. To address this issue, we develop a unified …
Asymptotic Properties Of Least Squares Estimator In Local To Unity Processes With Fractional Gaussian Noises, Xiaohu Wang, Weilin Xiao, Jun Yu
Asymptotic Properties Of Least Squares Estimator In Local To Unity Processes With Fractional Gaussian Noises, Xiaohu Wang, Weilin Xiao, Jun Yu
Research Collection School Of Economics
This paper derives asymptotic properties of the least squares estimator of the autoregressive parameter in local to unity processes with errors being fractional Gaussian noises with the Hurst parameter H 2 (0; 1). It is shown that the estimator is consistent for all values of H 2 (0; 1). Moreover, the rate of convergence is n 1 when H 2 [0:5; 1). The rate of convergence is n 2H when H 2 (0; 0:5). Furthermore, the limiting distribution of the centered least squares estimator depends on H. When H = 0:5, the limiting distribution is the same as that obtained …