Econometrics Commons^™

Analysis Of U.S. Housing Markets Using Advanced Econometric Models And Machine Learning Algorithms, Cody Kirby

Dissertations

The Great Recession is the most recent reminder in U.S. history of the important relationship that exists between monetary policy and housing market activity. Since World War II, eight U.S. recessions have followed downturns in housing. A decline in the housing market results in the balance sheet deterioration of homeowners, financial institutions, private organizations, central banks, governing bodies, and foreign countries. The ability to understand the relationship between monetary policy and housing market activity, and to better forecast housing prices, allows for better planning by all economic agents.

This study answers the following research questions. (1) How have monetary policy …

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 …

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 …

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 …

Deciding For Others: Local Public Good Contributions With Intermediaries, Andrej Angelovski, Praveen Kujal, Christos Mavridis

ESI Working Papers

Given the prevalence of local public goods, whose broader use is often limited by distance and borders, we propose a potential solution to the free-riding problem by having each participant/beneficiary delegate the public good contribution decision to a non-local intermediary who neither puts in own endowment into the public good nor benefits from it. Intermediaries make decisions under two compensation mechanisms where the incentives for the intermediary are either non-aligned (fixed) or aligned (variable) with those of the beneficiary. We find that the use of intermediaries, regardless of whether their compensation is aligned or not with that of the beneficiary, …

Choice Flexibility And Long-Run Cooperation, Gabriele Camera, Jaehong Kim, David Rojo Arjona

ESI Working Papers

Cooperation does not empirically scale when strangers confront indefinitely repeated social dilemmas—despite its incentive-compatibility. Here, we investigate if an intervention can mitigate this problem: expanding the action set with partial cooperation choices. Although standard theory predicts no effect, adding interior choices to a rigid binary-choice game often boosted cooperation and efficiency in the laboratory. Under some conditions, groups of strangers achieved outcomes close to those observed in pairs of partners—where adding interior choices, instead, was inconsequential. This suggests that choice rigidities can hinder long-run cooperation.

Failed Secular Revolutions: Religious Belief, Competition, And Extremism, Jean-Paul Carvalho, Jared Rubin, Michael Sacks

ESI Working Papers

All advanced economies have undergone secular revolutions in which religious belief and institutions have been subordinated to secular forms of authority. There are, however, numerous examples of failed secular transitions. To understand these failures, we present a religious club model with endogenous entry and cultural transmission of religious beliefs. A spike in the demand for religious belief, due for example to a negative economic shock, induces a new and more extreme organization to enter the religious market and exploit the dissatisfaction of highly religious types with the religious incumbent. The eect is larger where institutional secularization is more advanced, for …

Modeling And Forecasting Inflation Rate In Nigeria: A Comparison Of Regression With Arima Errors And Arima Method, Barthelomew I. Ugwuanyi

Bullion

The paper aimed to determine the most appropriate method for forecasting inflation rate in Nigeria between Regression with Autoregressive Integrated Moving Average (ARIMA) errors and Autoregressive Integrated Moving Average (ARIMA) method. This study uses annual data for the period 1990-2021 from World Bank. One response variable and three predictor variables are adopted. The best ARIMA method was selected from the competing ARIMA methods using Akaike Information Criterion Corrected (AICC), while the root mean squared error (RMSE) and mean absolute percentage error (MAPE) are used to select the best forecast method between the two methods of interest. The result of this …

Assessment Of Fuel Prices As Determinants Of Inflation In Nigeria: A Vecm Approach, Adekunle B. Alexander Dr., Pelumi A. Abdulmalik

Bullion

This study examines the effect of petroleum price on the direction of inflation in Nigeria - whether or not movement in prices of other goods and services responds to increase in pump price of premium motor spirit (PMS) otherwise known as petrol in Nigeria. The study employs the Vector Error Correction Model (VECM) and Granger causality tests to estimate the long-run relationship between petro! price and inflation as well as direction of causality for the 1991- 2021 period. Data for the study were sourced from the National Bureau of Statistics (NBS) and World Bank data indicators covering inflation, pump-price of …

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 …

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 …

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.

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 …

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 …

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 …

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 …

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 …

Competing Social Influence In Contested Diffusion: Luther, Erasmus And The Spread Of The Protestant Reformation, Sascha O. Becker, Steven Pfaff, Yuan Hsiao, Jared Rubin

ESI Working Papers

The spread of radical institutional change does not often result from one-sided pro-innovation influence; countervailing influence networks in support of the status quo can suppress adoption. We develop a model of multiple and competing network diffusion. To apply the contested-diffusion model to real data, we look at the contest between Martin Luther and Desiderius Erasmus, the two most influential intellectuals of early 16th-century Central Europe. Whereas Luther championed a radical reform of the Western Church that broke with Rome, Erasmus opposed him, stressing the unity of the Church. In the early phase of the Reformation, these two figures utilized influence …

An Experimental Test Of Algorithmic Dismissals, Brice Corgnet

ESI Working Papers

We design a laboratory experiment in which a human or an algorithm decides which of two workers to dismiss. The algorithm automatically dismisses the least productive worker whereas human bosses have full discretion over their decisions. Using performance metrics and questionnaires, we find that fired workers react more negatively to human than to algorithmic decisions in a broad range of tasks. We show that spitefulness exacerbated this negative reaction. Our findings suggest algorithms could help tame negative reactions to dismissals.

The Methodology Of Multiple Regressions For Gdp Per Capita For Nations In The World Between 0 Ce And 1940, Robert Rogers

The Journal of Economics and Politics

A reduced-form model of GDP per capita is estimated using the classical econometric method and two Bayesian techniques, Extreme Bounds Analysis (EBA) and Bayesian Analysis of Classical Estimation (BACE) for the two millenniums. For several variables, such as the impact of colonialism, the Goldstone hypothesis of efflorescence increasing economic growth, and the impact of technology, this paper lends support, especially when the Bayesian methods are applied. Other results are mixed. Generally, the results support use of Bayesian methods by eliminating hypotheses that are not consistently supported over all models.