Research - Bo Hu

Analysis of Distributional Dynamics for Repeated Cross-Sectional and Intra-Period Observations (with Joon Y. Park and Junhui Qian)
R&R at Journal of Econometrics

This paper introduces a novel approach to investigate the dynamics of state distributions, which accommodate both cross-sectional distributions of repeated panels and intra-period distributions of a time series observed at high frequency. In our approach, densities of the state distributions are regarded as functional elements in a Hilbert space, and are assumed to follow a functional autoregressive model. We propose an estimator for the autoregressive operator, establish its consistency, and provide tools and asymptotics to analyze the forecast of state density and the moment dynamics of state distributions. We apply our methodology to study the time series of intra-month return distributions of the GBP/USD exchange rate and the time series of cross-sectional distributions of the NYSE stocks monthly returns. We also evaluate by simulations the density forecasts based on our model.

Econometric Analysis of Persistent Functional Dynamics (with Yoosoon Chang and Joon Y. Park)

We introduce an autoregressive model for functional time series with unit roots. The autoregressive operator can be consistently estimated, but its convergence rate and limit distribution are different in different subspaces. In the unit root subspace, the convergence rate is fast and given by \(n\), while the limit distribution is nonstandard and represented as functions of Brownian motions. Outside the unit root subspace, however, the limit distribution is Gaussian, although the convergence rate varies and is given by \(\sqrt{n}\) or a slower rate.The predictor based on the estimated autoregressive operator has a normal limit distribution with a reduced rate of convergence. We also provide the Beveridge-Nelson decomposition, which identifies the permanent and transitory components of functional time series with unit roots, representing persistent stochastic trends and stationary cyclical movements, respectively. Using our methodology and theory, we analyze the time series of yield curves and study the dynamics of the term structure of interest rates.

Asymptotics of Functional Spectral Component Analysis with Weakly Dependent Data
Available Soon Slides

I develop the asymptotic theory for principal spectral analysis of weakly dependent functional data in a separable Hilbert space. Principal spectral analysis is the analysis on statistical quantities that are representable by spectral characteristics of certain operators that are used to summarize the data. Principal spectral analysis includes, but is not limited to, the prominent example of principal component analysis. I give examples of principal spectral analysis with functional data, and with a version of the functional central limit theorem, we show how we may establish the limit distributions of quantities in principal spectral analysis in a unified framework, allowing the functional data to be weakly dependent.

On the Error Correction Model for Functional Time Series with Unit Roots (with Yoosoon Chang and Joon Y. Park)

This paper studies the error correction model for functional time series with unit roots, which generalizes the vector error correction model for finite dimensional time series with unit roots. We unravel two important facts on the functional error correction model. First, any functional time series generated by an error correction model with a compact error correction operator has infinite dimensional unit roots. Second, the Granger’s representation theorem continues to hold for the functional time series with unit roots in a form essentially identical to that for the finite dimensional error correction model.

Accounting for Individual-Specific Heterogeneity in Intergenerational Income Mobility (with Yoosoon Chang, Steven Durlauf and Joon Y. Park)

This paper proposes a fully nonparametric model to investigate the dynamics of intergenerational income mobility. In our model, an individual’s income class probabilities depend on parental income in a manner that accommodates nonlinearities and interactions among various individual characteristics and parental characteristics, including race, education, and parental age at childbearing. Consequently, we offer a generalization of Markov chain mobility models. We employ kernel techniques from machine learning and further regularization for estimating this highly flexible model. Utilizing data from the Panel Study of Income Dynamics (PSID), we find that race and parental education play significant roles in determining the influence of parental income on children’s economic prospects.

Incentives, Policy Burdens and Supervision Intensity: Some Lessons from the Chinese SOE Reforms (with Justin Yifu Lin and Jinaye Yan)

The past forty years have witnessed the high-speed growth of Chinese economy. Together with the economy growth is the continuous reform of the Chinese state-owned enterprises (SOEs). We first review the main three waves of SOEs reform, which all took a gradual format, first experimented in selected enterprises, once successful, then promoted to the vast majority. Despite the success in the selected pilots, the effect of each wave became less satisfactory after popularization. We reinvestigate these reforms under the perspective of incentive design. The policy burdens that SOEs undertook led to the issue of soft budget constraint. With the separation of ownership and control, moral hazard arose and possible opportunistic behaviors from the managers and workers of the SOEs could appear. In the experiment stage, since each firm faced extraordinary supervision, opportunistic behaviors were suppressed, and the government sees an increased profit. Once more firms got involved in the reform and the supervision intensity was diluted, opportunistic behaviors dominated, and the government saw a failure of the reform.

Long-Term Finance Provision: National Development Banks VS. Commercial Banks (with Alfredo Schclarek, Jiajun Xu, and Jianye Yan)
World Development

This paper examines whether national development banks (NDBs) lend longer than commercial banks. Using a new, hand-collected dataset on development finance institutions worldwide matched with the bank-level data from BankFocus, we find that the maturity of NDB loans is higher than that of commercial bank loans and this finding is statistically significant after controlling for macroeconomic and bank-level factors. Furthermore, we find that NDBs in middle-income countries are more likely to provide long-term loans that those in low-income countries or high-income countries. Our paper suggests potential explanatory variables in explaining this stylized fact.

A Full Characterization of Integrated and Cointegrated VAR Systems
Industrial Structure and Monetary Policy
Government Investment and Monetary-Fiscal Policy Interactions
Interest Rate Differential between Bonds Issued by Private Commercial Banks and State-Owned Commercial Banks and National Development Banks, with Jiajun Xu and Alfredo Schclarek
Growth Accounting in a Catching-up Developing Economy, with Justin Yifu Lin
SOE Reforms and Subsidies, with Justin Yifu Lin
Measure of Development Strategy Distortion, with Xin Wang
Financial Repression and Interest Rate Liberalization in China