J. Miller

发表

Testing for Cointegration with Temporally Aggregated and Mixed‐Frequency Time Series

E. Ghysels, J. Miller, Eric Ghysels, 2013 .

Testing Cointegrating Relationships Using Irregular and Non‐Contemporaneous Series with an Application to Paleoclimate Data

J. Miller, J. Miller, 2019, Journal of Time Series Analysis.

On the spatial correlation of international conflict initiation and other binary and dyadic dependent variables

J. Miller, Shali Luo, J. Isaac Miller, 2014 .

Time-varying Long-run Income and Output Elasticities of Electricity Demand

Chang Sik Kim, Sungkeun Park, J. Miller, 2014 .

Beyond RCP8.5: Marginal mitigation using quasi-representative concentration pathways

W. Brock, J. Miller, J. Miller, 2021, Journal of Econometrics.

LONG-TERM OIL PRICE FORECASTS: A NEW PERSPECTIVE ON OIL AND THE MACROECONOMY

J. Isaac Miller, Shawn Ni, J. Miller, 2011, Macroeconomic Dynamics.

Nonlinearity, nonstationarity, and thick tails: How they interact to generate persistence in memory☆

J. Miller, Joon Y. Park, J. Miller, 2010 .

Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures

J. Miller, J. Miller, 2014 .

Estimating a Cointegrating Regression with Missing Data

J. Miller, 2007 .

Modeling peak electricity demand: A semiparametric approach using weather-driven cross-temperature response functions

J. Miller, K. Nam, J. Miller, 2022, Energy Economics.

Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series

J. Miller, 2016 .

On the Size Distortion from Linearly Interpolating Low-frequency Series for Cointegration Tests

J. Miller, Eric Ghysels, J. Miller, 2014 .

A Nonlinear IV Likelihood-Based Rank Test for Multivariate Time Series and Long Panels

J. Miller, 2010 .

Crude oil and stock markets: Stability, instability, and bubbles ☆

J. Isaac Miller, J. Miller, Ronald A. Ratti, 2009 .

Extracting a common stochastic trend: Theory with some applications

J. Miller, Yoosoon Chang, Joon Y. Park, 2009 .

Simple Robust Tests for the Specification of High-Frequency Predictors of a Low-Frequency Series

J. Isaac Miller, J. Miller, 2018 .

Cointegrating MiDaS Regressions and a MiDaS Test

J. Miller, J. Miller, 2011 .

Cointegrating Regressions with Messy Regressors: Missingness, Mixed Frequency, and Nonclassical Measurement Error

J. Miller, J. Miller, 2009 .

A new approach to modeling the effects of temperature fluctuations on monthly electricity demand

Chang Sik Kim, Sungkeun Park, J. Miller, 2016 .

Dating hiatuses: a statistical model of the recent slowdown in global warming and the next one

J. Miller, K. Nam, J. Miller, 2020 .

Forecasting regional long-run energy demand: A functional coefficient panel approach

Chang Sik Kim, J. Isaac Miller, Joon Y. Park, 2021, Energy Economics.

Disentangling temporal patterns in elasticities: A functional coefficient panel analysis of electricity demand

J. Miller, Yoosoon Chang, Joon Y. Park, 2016 .

Implementing Residual‐Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies

J. Miller, Xi Wang, 2016 .

Testing the Bounds: Empirical Behavior of Target Zone Fundamentals

J. Miller, J. Miller, 2011 .

Local Climate Sensitivity: A Statistical Approach for a Spatially Heterogeneous Planet

J. Miller, J. Miller, 2017 .