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Research Collection School Of Economics

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Full-Text Articles in Econometrics

Connecting The (Dirty) Dots: Current Account Surplus And Polluting Production, Jungho Lee, Shang-Jin Wei, Jianhuan Xu Oct 2023

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.

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Self-Financing, Parental Transfer, And College Education, Jungho Lee, Sunha Myong Sep 2023

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.

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Spatial Disaggregation Of Poverty And Disability: Application To Tanzania, Tomoki Fujii Aug 2023

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.

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Common Bubble Detection In Large Dimensional Financial Systems, Ye Chen, Peter C. B. Phillips, Shuping Shi Aug 2023

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 …

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Volatility Puzzle: Long Memory Or Anti-Persistency, Shuping Shi, Jun Yu Jul 2023

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 …

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Multivariate Stochastic Volatility Models Based On Generalized Fisher Transformation, Han Chen, Yijie Fei, Jun Yu Jul 2023

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 …

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The Impact Of Upzoning On Housing Construction In Auckland*, Ryan Greenaway-Mcgrevy, Peter C. B. Phillips Jul 2023

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 …

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Bootstrapping Two-Stage Quasi-Maximum Likelihood Estimators Of Time Series Models, Sílvia Gonçalves, Ulrich Hounyo, Andrew John Patton, Kevin Sheppard Jul 2023

Bootstrapping Two-Stage Quasi-Maximum Likelihood Estimators Of Time Series Models, Sílvia Gonçalves, Ulrich Hounyo, Andrew John Patton, Kevin Sheppard

Research Collection School Of Economics

This article provides results on the validity of bootstrap inference methods for two-stage quasi-maximum likelihood estimation involving time series data, such as those used for multivariate volatility models or copula-based models. Existing approaches require the researcher to compute and combine many first- and second-order derivatives, which can be difficult to do and is susceptible to error. Bootstrap methods are simpler to apply, allowing the substitution of capital (CPU cycles) for labor (keeping track of derivatives). We show the consistency of the bootstrap distribution and consistency of bootstrap variance estimators, thereby justifying the use of bootstrap percentile intervals and bootstrap standard …

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Regression-Adjusted Estimation Of Quantile Treatment Effects Under Covariate-Adaptive Randomizations, Liang Jiang, Peter C. B. Phillips, Yubo Tao, Yichong Zhang Jun 2023

Regression-Adjusted Estimation Of Quantile Treatment Effects Under Covariate-Adaptive Randomizations, Liang Jiang, Peter C. B. Phillips, Yubo Tao, Yichong Zhang

Research Collection School Of Economics

Datasets from field experiments with covariate-adaptive randomizations (CARs) usually contain extra covariates in addition to the strata indicators. We propose to incorporate these additional covariates via auxiliary regressions in the estimation and inference of unconditional quantile treatment effects (QTEs) under CARs. We establish the consistency and limit distribution of the regression-adjusted QTE estimator and prove that the use of multiplier bootstrap inference is non-conservative under CARs. The auxiliary regression may be estimated parametrically, nonparametrically, or via regularization when the data are high-dimensional. Even when the auxiliary regression is misspecified, the proposed bootstrap inferential procedure still achieves the nominal rejection probability …

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Disagreement In Market Index Options, Guilherme Salome, George Tauchen, Jia Li Jun 2023

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 …

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Economic Forecasting In A Pandemic: Some Evidence From Singapore, Hwee Kwan Chow-Tan, Keen Meng Choy May 2023

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 …

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Improved Marginal Likelihood Estimation Via Power Posteriors And Importance Sampling, Yong Li, Nianling Wang, Jun Yu May 2023

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 …

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On The Spectral Density Of Fractional Ornstein-Uhlenbeck Process: Approximation, Estimation, And Model Comparison, Shuping Shi, Jun Yu, Chen Zhang May 2023

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 …

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Inflation Dynamics And Expectations In Singapore, Hwee Kwan Chow-Tan May 2023

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 …

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Uniform Nonparametric Inference For Time Series Using Stata, Jia Li, Zhipeng Liao, Mengsi Gao May 2023

Uniform Nonparametric Inference For Time Series Using Stata, Jia Li, Zhipeng Liao, Mengsi Gao

Research Collection School Of Economics

In this article, we introduce a command, tssreg, that conducts nonparametric series estimation and uniform inference for time-series data, including the case with independent data as a special case. This command can be used to nonparametrically estimate the conditional expectation function and the uniform confidence band at a user-specified confidence level, based on an econometric theory that accommodates general time-series dependence. The uniform inference tool can also be used to perform nonparametric specification tests for conditional moment restrictions commonly seen in dynamic equilibrium models.

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Asymptotic Properties Of Least Squares Estimator In Local To Unity Processes With Fractional Gaussian Noises, Xiaohu Wang, Weilin Xiao, Jun Yu Apr 2023

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 …

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Estimation And Inference With Near Unit Roots, Peter C. B. Phillips Apr 2023

Estimation And Inference With Near Unit Roots, Peter C. B. Phillips

Research Collection School Of Economics

New methods are developed for identifying, estimating, and performing inference with nonstationary time series that have autoregressive roots near unity. The approach subsumes unit-root (UR), local unit-root (LUR), mildly integrated (MI), and mildly explosive (ME) specifications in the new model formulation. It is shown how a new parameterization involving a localizing rate sequence that characterizes departures from unity can be consistently estimated in all cases. Simple pivotal limit distributions that enable valid inference about the form and degree of nonstationarity apply for MI and ME specifications and new limit theory holds in UR and LUR cases. Normalizing and variance stabilizing …

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Adjustment With Many Regressors Under Covariate-Adaptive Randomizations, Liang Jiang, Liyao Li, Ke Miao, Yichong Zhang Apr 2023

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 …

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Cities In A Pandemic: Evidence From China, Badi H. Baltagi, Ying Deng, Li Jing, Zhenlin Yang Mar 2023

Cities In A Pandemic: Evidence From China, Badi H. Baltagi, Ying Deng, Li Jing, Zhenlin Yang

Research Collection School Of Economics

This paper studies the impact of urban density, city government efficiency, and medical resources on COVID-19 infection and death outcomes in China. We adopt a simultaneous spatial dynamic panel data model to account for (i) the simultaneity of infection and death outcomes, (ii) the spatial pattern of the transmission, (iii) the intertemporal dynamics of the disease, and (iv) the unobserved city-specific and time-specific effects. We find that, while population density increases the level of infections, government efficiency significantly mitigates the negative impact of urban density. We also find that the availability of medical resources improves public health outcomes conditional on …

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Hypothesis Testing Via Posterior-Test-Based Bayes Factors, Yong Li, Nianling Wang, Jun Yu, Yonghui Zhang Mar 2023

Hypothesis Testing Via Posterior-Test-Based Bayes Factors, Yong Li, Nianling Wang, Jun Yu, Yonghui Zhang

Research Collection School Of Economics

Hypothesis testing via p-value has been criticized in recent years. Bayes factors (BFs) have been tipped as a possible replacement of p-value for hypothesis testing. However, the standard BFs suffer from some theoretical and practical difficulties. For example, they are not well defined under improper priors and are subject to Jeffreys-Lindley-Bartlett’s paradox under vague priors. Moreover, they are difficult to compute for many models. In this paper, we propose to compare sampling distributions of the posterior-test-based statistics for hypothesis testing. Two posterior-test-based BFs are constructed from the posterior version of the likelihood ratio test and the Wald test, respectively. Under …

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Asymptotic Theory For Explosive Fractional Ornstein–Uhlenbeck Processes, Hui Jiang, Yajuan Pan, Weilin Liao, Qingshan Yang, Jun Yu Mar 2023

Asymptotic Theory For Explosive Fractional Ornstein–Uhlenbeck Processes, Hui Jiang, Yajuan Pan, Weilin Liao, Qingshan Yang, Jun Yu

Research Collection School Of Economics

This paper proposes estimators for the parameters of an explosive fractional Ornstein-Uhlenbeck process. The asymptotic properties for the diffusion estimators are developed under the in-fill asymptotic scheme, while the asymptotic properties for the drift estimators are developed under the double asymptotic scheme for the full range of the Hurst parameter. Simulation results demonstrate the effectiveness of the proposed estimators, and the asymptotic distributions provide a good approximation in finite samples. Empirical applications are presented to demonstrate the model’s usefulness and the practical value of the asymptotic theory.

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Fully Modified Least Squares Cointegrating Parameter Estimation In Multicointegrated Systems, Igor L. Kheifets, Peter C. B. Phillips Feb 2023

Fully Modified Least Squares Cointegrating Parameter Estimation In Multicointegrated Systems, Igor L. Kheifets, Peter C. B. Phillips

Research Collection School Of Economics

Multicointegration is traditionally defined as a particular long run relationship among variables in a parametric vector autoregressive model that introduces additional cointegrating links between these variables and partial sums of the equilibrium errors. This paper departs from the parametric model, using a semiparametric formulation that reveals the explicit role that singularity of the long run conditional covariance matrix plays in determining multicointegration. The semiparametric framework has the advantage that short run dynamics do not need to be modeled and estimation by standard techniques such as fully modified least squares (FM-OLS) on the original system is straightforward. The paper derives FM-OLS …

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Modeling And Forecasting Realized Volatility With The Fractional Ornstein-Uhlenbeck Process, Xiaohu Wang, Weilin Xiao, Jun Yu Feb 2023

Modeling And Forecasting Realized Volatility With The Fractional Ornstein-Uhlenbeck Process, Xiaohu Wang, Weilin Xiao, Jun Yu

Research Collection School Of Economics

This paper proposes to model and forecast realized volatility (RV) using the fractional Ornstein-Uhlenbeck (fO-U) process with a general Hurst parameter, H. A two-stage method is introduced for estimating parameters in the fO-U process based on discrete-sampled observations. In the first stage, H is estimated based on the ratio of two second-order differences of observations from different frequencies. In the second stage, with the estimated , the other parameters of the model are estimated by the method of moments. All estimators have closed-form expressions and are easy to implement. A large sample theory of the proposed estimators is derived. Extensive …

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Covariate Adjustment In Experiments With Matched Pairs, Yuehao Bai, Liang Jiang, Joseph P. Romano, Azeem M. Shaikh, Yichong Zhang Feb 2023

Covariate Adjustment In Experiments With Matched Pairs, Yuehao Bai, Liang Jiang, Joseph P. Romano, Azeem M. Shaikh, Yichong Zhang

Research Collection School Of Economics

This paper studies inference on the average treatment effect in experiments in which treatment status is determined according to “matched pairs” and it is additionally desired to adjust for observed, baseline covariates to gain further precision. By a “matched pairs” design, we mean that units are sampled i.i.d. from the population of interest, paired according to observed, baseline covariates and finally, within each pair, one unit is selected at random for treatment. Importantly, we presume that not all observed, baseline covariates are used in determining treatment assignment. We study a broad class of estimators based on a “doubly robust” moment …

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Diagnosing Housing Fever With An Econometric Thermometer, Shuping Shi, Peter C. B. Phillips Feb 2023

Diagnosing Housing Fever With An Econometric Thermometer, Shuping Shi, Peter C. B. Phillips

Research Collection School Of Economics

Housing fever is a popular term to describe an overheated housing market or housing price bubble. Like other financial asset bubbles, housing fever can inflict harm on the real economy, as indeed the U.S. housing bubble did in the period following 2006 leading up to the general financial crisis and great recession. One contribution that econometricians can make to minimize the harm created by a housing bubble is to provide a quantitative “thermometer” for diagnosing ongoing housing fever. Early diagnosis can enable prompt and effective policy action that reduces long-term damage to the real economy. This paper provides a selective …

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When Bias Contributes To Variance: True Limit Theory In Functional Coefficient Cointegrating Regression, Peter C. B. Phillips, Ying Wang Feb 2023

When Bias Contributes To Variance: True Limit Theory In Functional Coefficient Cointegrating Regression, Peter C. B. Phillips, Ying Wang

Research Collection School Of Economics

Limit distribution theory in the econometric literature for functional coefficient cointegrating regression is incorrect in important ways, influencing rates of convergence, distributional properties, and practical work. The correct limit theory reveals that components from both bias and variance terms contribute to variability in the asymptotics. The errors in the literature arise because random variability in the bias term has been neglected in earlier research. In stationary regression this random variability is of smaller order and can be ignored in asymptotic analysis but not without consequences for finite sample performance. Implications of the findings for rate efficient estimation are discussed. Simulations …

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Permutation-Based Tests For Discontinuities In Event Studies, Federico Bugni, Jia Li, Qiyuan Li Jan 2023

Permutation-Based Tests For Discontinuities In Event Studies, Federico Bugni, Jia Li, Qiyuan Li

Research Collection School Of Economics

We propose using a permutation test to detect discontinuities in an underlying economic model at a cutoff point. Relative to the existing literature, we show that this test is well suited for event studies based on time-series data. The test statistic measures the distance between the empirical distribution functions of observed data in two local subsamples on the two sides of the cutoff. Critical values are computed via a standard permutation algorithm. Under a high-level condition that the observed data can be coupled by a collection of conditionally independent variables, we establish the asymptotic validity of the permutation test, allowing …

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Can Digital Finance Promote Low-Carbon Transition? Evidence From China, Xing Ge, Tomoki Fujii Jan 2023

Can Digital Finance Promote Low-Carbon Transition? Evidence From China, Xing Ge, Tomoki Fujii

Research Collection School Of Economics

Using panel data of Chinese cities from 2011 to 2019, this paper analyzes the impact of digital finance on low-carbon transition derived from a super-efficiency slacks-based measure data envelopment analysis. We find that digital finance promotes low-carbon transition, and this finding is robust with respect to the choice of sample, potential presence of measurement issue, choice of study period, presence of other policies, and potential endogeneity, among others. This impact is at least in part goes through increased green innovations. We also find evidence for impact heterogeneity across locations and by the level of low-carbon transition.

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Conditional Evaluation Of Predictive Models: The Cspa Command, Jia Li, Zhipeng Liao, Rogier Quaedvlieg, Wenyu Zhou Jan 2023

Conditional Evaluation Of Predictive Models: The Cspa Command, Jia Li, Zhipeng Liao, Rogier Quaedvlieg, Wenyu Zhou

Research Collection School Of Economics

In this article, we introduce a new command, cspa, that implements the conditional superior predictive ability test developed in Li, Liao, and Quaedvlieg (2022, Review of Economic Studies 89: 843–875). With the conditional performance of predictive methods measured nonparametrically by the conditional expectation functions of their predictive losses, we test the null hypothesis that a benchmark model weakly outperforms a collection of competitors uniformly across the conditioning space. The proposed command can implement this test for both independent cross-sectional data and serially dependent time-series data. Confidence sets for the most superior model can be obtained by inverting the test, for …

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A Mixture Autoregressive Model Based On Student’S T–Distribution, Mika Meitz, Daniel Preve, Pentti Saikkonen Jan 2023

A Mixture Autoregressive Model Based On Student’S T–Distribution, Mika Meitz, Daniel Preve, Pentti Saikkonen

Research Collection School Of Economics

A new mixture autoregressive model based on Student’s t–distribution is proposed. A key feature of our model is that the conditional t–distributions of the component models are based on autoregressions that have multivariate t–distributions as their (low-dimensional) stationary distributions. That autoregressions with such stationary distributions exist is not immediate. Our formulation implies that the conditional mean of each component model is a linear function of past observations and the conditional variance is also time-varying. Compared to previous mixture autoregressive models our model may therefore be useful in applications where the data exhibits rather strong conditional heteroskedasticity. Our formulation also has …

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