Lutz Kilian
Biographic Data
| ID | 1157053 |
|---|---|
| NAME | Lutz Kilian |
| GIVEN NAMES | Lutz |
| FAMILY NAME | Kilian |
| SIGNATURE | KILIAN L |
| AFFILIATIONS | University of Michigan |
| VERIFIED | No |
| TOTAL WORKS | 23 |
| TOTAL CITATIONS | 30 |
| AUTHOR COUNT | 23 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1998 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
Estimating Macroeconomic News and Surprise Shocks
A common VAR approach is to identify responses to TFP news shocks by maximizing the variance share of TFP over a long horizon. We find that these TFP max share estimators tend to be biased in large samples when applied to data generated from DSGE models with shock processes that match TFP moments in the data, especially in the presence of TFP measurement error. We propose an alternative max share news estimator that reduces this bias and the RMSE…
The Conventional Impulse Response Prior in VAR Models With Sign Restrictions
Some studies have expressed concern that the Gaussian‐inverse Wishart–Haar prior typically employed in estimating sign‐identified VAR models may be unintentionally informative about the prior for the structural responses. We discuss what features to look for in this prior in the absence of specific prior information about the responses, building on the notion of weakly informative priors in Gelman et al. (2013), and in the presence of such inform…
Macroeconomic Responses to Uncertainty Shocks: The Perils of Recursive Orderings
A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autoregressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of unc…
When Is the Use of Gaussian-Inverse Wishart-Haar Priors Appropriate
Oil prices, gasoline prices, and inflation expectations
It has long been suspected, given the salience of gasoline prices, that fluctuations in gasoline prices shift households' 1‐year inflation expectations. Assessing this view empirically requires the use of dynamic structural models to quantify the cumulative effect of gasoline price shocks on household inflation expectations at each point in time. We find that, on average, gasoline price shocks account for 42% of the variation in these expectation…
Does drawing down the US Strategic Petroleum Reserve help stabilize oil prices
We study the effects of releases from the US Strategic Petroleum Reserve (SPR) within the context of fully specified models of the global oil market that explicitly allow for storage demand as well as unanticipated changes in the SPR. We show that historically SPR policy interventions, defined as sequences of exogenous SPR shocks during selected periods, have helped stabilize the price of oil. Their effect on the price of oil, however, has been m…
Structural Vector Autoregressive Analysis
Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book …
Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us
It has been 40 years since the oil crisis of 1973/74. This crisis has been one of the defining economic events of the 1970s and has shaped how many economists think about oil price shocks. In recent years, a large literature on the economic determinants of oil price fluctuations has emerged. Drawing on this literature, we first provide an overview of the causes of all major oil price fluctuations between 1973 and 2014. We then discuss why oil pri…
Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach
The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly forecasts of the price of crude oil for horizons up to 2 years, which are widely used by practitioners. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify. An alternative is the use of real-time econometric oil price forecasting models. We investigate the merits of constructing combinatio…
The Role of Inventories and Speculative Trading in the Global Market for Crude Oil
We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative …
Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries
There is a long tradition of using oil prices to forecast U.S. real GDP. It has been suggested that the predictive relationship between the price of oil and one-quarter-ahead U.S. real GDP is nonlinear in that (a) oil price increases matter only to the extent that they exceed the maximum oil price in recent years, and that (b) oil price decreases do not matter at all. We examine, first, whether the evidence of in-sample predictability in support …
Real-Time Forecasts of the Real Price of Oil
We construct a monthly real-time dataset consisting of vintages for 1991.1–2010.12 that is suitable for generating forecasts of the real price of oil from a variety of models. We document that revisions of the data typically represent news, and we introduce backcasting and nowcasting techniques to fill gaps in the real-time data. We show that real-time forecasts of the real price of oil can be more accurate than the no-change forecast at horizons…
How Reliable Are Local Projection Estimators of Impulse Responses
We compare the finite-sample performance of impulse response confidence intervals based on local projections (LPs) and vector autoregressive (VAR) models in linear stationary settings. We find that in small samples, the asymptotic LP interval often is less accurate than the bias-adjusted bootstrap VAR interval, notwithstanding its excessive average length. Although the asymptotic LP interval has adequate coverage in sufficiently large samples, it…
Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices
We propose a formal test of the hypothesis that energy prices are predetermined with respect to U.S. macroeconomic aggregates. The test is based on regressing changes in daily energy prices on daily news from U.S. macroeconomic data releases. Using a wide range of macroeconomic news, we find no compelling evidence of feedback at daily or monthly horizons, contradicting the view that energy prices respond instantaneously to macroeconomic news and …
The Allocative Cost of Price Ceilings in the U.S. Residential Market for Natural Gas
A direct consequence of imposing a ceiling on the price of a good for which secondary markets do not exist, is that, when there is excess demand, the good will not be allocated to the buyers who value it the most. The resulting allocative cost has been discussed in the literature as a potentially important component of the total welfare loss from price ceilings, but its practical importance has yet to be established empirically. In this paper, we…
Does the Fed Respond to Oil Price Shocks
A common view in the literature is that systematic monetary policy responses to the inflation caused by oil price shocks have been an important source of aggregate fluctuations in the US economy. Earlier empirical evidence in support of such a link was based on inappropriate econometric models. We show that there is no credible evidence that monetary policy responses to oil price shocks caused large aggregate fluctuations in the 1970s and 1980s o…
Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market
Shocks to the real price of oil may reflect oil supply shocks, shocks to the global demand for all industrial commodities, or demand shocks that are specific to the crude oil market. Each shock has different effects on the real price of oil and on US macroeconomic aggregates. Changes in the composition of shocks help explain why regressions of macroeconomic aggregates on oil prices tend to be unstable. Evidence that the recent surge in oil prices…
Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy
The paper proposes a new measure of exogenous oil supply shocks. The timing, the magnitude, and the sign of this measure may differ greatly from current state-of-the-art estimates. It is shown that only a small fraction of the observed oil price increases during oil crisis periods can be attributed to exogenous oil production disruptions. Exogenous oil supply shocks cause a sharp drop of U.S. real GDP growth after five quarters rather than an imm…
Oil and the Macroeconomy Since the 1970s
Increases in oil prices have been held responsible for recessions, periods of excessive inflation, reduced productivity and lower economic growth. In this paper, we review the arguments supporting such views. First, we highlight some of the conceptual difficulties in assigning a central role to oil price shocks in explaining macroeconomic fluctuations, and we trace how the arguments of proponents of the oil view have evolved in response to these …
Unit-Root Tests Are Useful for Selecting Forecasting Models
We study the usefulness of unit-root tests as diagnostic tools for selecting forecasting models. Difference-stationary and trend-stationary models of economic and financial time series often imply very different predictions, so deciding which model to use is tremendously important for applied forecasters. We consider three strategies: Always difference the data, never difference, or use a unit-root pretest. We characterize the predictive loss of …
Residual-Based Tests for Normality in Autoregressions: Asymptotic Theory and Simulation Evidence
Existing results for the asymptotic validity of the Jarque-Bera test in vector autoregressive (VAR) models assume stationarity. In applied work, however, researchers often work with possibly integrated and cointegrated process. We prove the asymptotic validity of the Jarque-Bera test for vector error-correction (VEC) models and for unrestricted VAR models with possibly integrated or cointegrated variables. We also propose the use of bootstrap cri…
Finite-Sample Properties of Percentile and Percentile- t Bootstrap Confidence Intervals for Impulse Responses
A Monte Carlo analysis of the coverage accuracy and average length of alternative bootstrap confidence intervals for impulse-response estimators shows that the accuracy of equal-tailed and symmetric percentile-t intervals can be poor and erratic in small samples (both in models with large roots and in models without roots near the unit circle). In contrast, some percentile bootstrap intervals may be both shorter and more accurate. The accuracy of…
Small-sample Confidence Intervals for Impulse Response Functions
Bias-corrected bootstrap confidence intervals explicitly account for the bias and skewness of the small-sample distribution of the impulse response estimator, while retaining asymptotic validity in stationary autoregressions. Monte Carlo simulations for a wide range of bivariate models show that in small samples bias-corrected bootstrap intervals tend to be more accurate than delta method intervals, standard bootstrap intervals, and Monte Carlo i…
Does the Fed Respond to Oil Price Shocks
A common view in the literature is that systematic monetary policy responses to the inflation caused by oil price shocks have been an important source of aggregate fluctuations in the US economy. Earlier empirical evidence in support of such a link was based on inappropriate econometric models. We show that there is no credible evidence that monetary policy responses to oil price shocks caused large aggregate fluctuations in the 1970s and 1980s o…
Oil and the Macroeconomy Since the 1970s
Increases in oil prices have been held responsible for recessions, periods of excessive inflation, reduced productivity and lower economic growth. In this paper, we review the arguments supporting such views. First, we highlight some of the conceptual difficulties in assigning a central role to oil price shocks in explaining macroeconomic fluctuations, and we trace how the arguments of proponents of the oil view have evolved in response to these …
The Allocative Cost of Price Ceilings in the U.S. Residential Market for Natural Gas
A direct consequence of imposing a ceiling on the price of a good for which secondary markets do not exist, is that, when there is excess demand, the good will not be allocated to the buyers who value it the most. The resulting allocative cost has been discussed in the literature as a potentially important component of the total welfare loss from price ceilings, but its practical importance has yet to be established empirically. In this paper, we…
Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us
It has been 40 years since the oil crisis of 1973/74. This crisis has been one of the defining economic events of the 1970s and has shaped how many economists think about oil price shocks. In recent years, a large literature on the economic determinants of oil price fluctuations has emerged. Drawing on this literature, we first provide an overview of the causes of all major oil price fluctuations between 1973 and 2014. We then discuss why oil pri…
Small-sample Confidence Intervals for Impulse Response Functions
Bias-corrected bootstrap confidence intervals explicitly account for the bias and skewness of the small-sample distribution of the impulse response estimator, while retaining asymptotic validity in stationary autoregressions. Monte Carlo simulations for a wide range of bivariate models show that in small samples bias-corrected bootstrap intervals tend to be more accurate than delta method intervals, standard bootstrap intervals, and Monte Carlo i…
Finite-Sample Properties of Percentile and Percentile- t Bootstrap Confidence Intervals for Impulse Responses
A Monte Carlo analysis of the coverage accuracy and average length of alternative bootstrap confidence intervals for impulse-response estimators shows that the accuracy of equal-tailed and symmetric percentile-t intervals can be poor and erratic in small samples (both in models with large roots and in models without roots near the unit circle). In contrast, some percentile bootstrap intervals may be both shorter and more accurate. The accuracy of…
Unit-Root Tests Are Useful for Selecting Forecasting Models
We study the usefulness of unit-root tests as diagnostic tools for selecting forecasting models. Difference-stationary and trend-stationary models of economic and financial time series often imply very different predictions, so deciding which model to use is tremendously important for applied forecasters. We consider three strategies: Always difference the data, never difference, or use a unit-root pretest. We characterize the predictive loss of …
Residual-Based Tests for Normality in Autoregressions: Asymptotic Theory and Simulation Evidence
Existing results for the asymptotic validity of the Jarque-Bera test in vector autoregressive (VAR) models assume stationarity. In applied work, however, researchers often work with possibly integrated and cointegrated process. We prove the asymptotic validity of the Jarque-Bera test for vector error-correction (VEC) models and for unrestricted VAR models with possibly integrated or cointegrated variables. We also propose the use of bootstrap cri…
Oil and the Macroeconomy Since the 1970s
Increases in oil prices have been held responsible for recessions, periods of excessive inflation, reduced productivity and lower economic growth. In this paper, we review the arguments supporting such views. First, we highlight some of the conceptual difficulties in assigning a central role to oil price shocks in explaining macroeconomic fluctuations, and we trace how the arguments of proponents of the oil view have evolved in response to these …
Exogenous Oil Supply Shocks: How Big Are They and How Much Do They Matter for the U.S. Economy
The paper proposes a new measure of exogenous oil supply shocks. The timing, the magnitude, and the sign of this measure may differ greatly from current state-of-the-art estimates. It is shown that only a small fraction of the observed oil price increases during oil crisis periods can be attributed to exogenous oil production disruptions. Exogenous oil supply shocks cause a sharp drop of U.S. real GDP growth after five quarters rather than an imm…
Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market
Shocks to the real price of oil may reflect oil supply shocks, shocks to the global demand for all industrial commodities, or demand shocks that are specific to the crude oil market. Each shock has different effects on the real price of oil and on US macroeconomic aggregates. Changes in the composition of shocks help explain why regressions of macroeconomic aggregates on oil prices tend to be unstable. Evidence that the recent surge in oil prices…
How Reliable Are Local Projection Estimators of Impulse Responses
We compare the finite-sample performance of impulse response confidence intervals based on local projections (LPs) and vector autoregressive (VAR) models in linear stationary settings. We find that in small samples, the asymptotic LP interval often is less accurate than the bias-adjusted bootstrap VAR interval, notwithstanding its excessive average length. Although the asymptotic LP interval has adequate coverage in sufficiently large samples, it…
Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices
We propose a formal test of the hypothesis that energy prices are predetermined with respect to U.S. macroeconomic aggregates. The test is based on regressing changes in daily energy prices on daily news from U.S. macroeconomic data releases. Using a wide range of macroeconomic news, we find no compelling evidence of feedback at daily or monthly horizons, contradicting the view that energy prices respond instantaneously to macroeconomic news and …
The Allocative Cost of Price Ceilings in the U.S. Residential Market for Natural Gas
A direct consequence of imposing a ceiling on the price of a good for which secondary markets do not exist, is that, when there is excess demand, the good will not be allocated to the buyers who value it the most. The resulting allocative cost has been discussed in the literature as a potentially important component of the total welfare loss from price ceilings, but its practical importance has yet to be established empirically. In this paper, we…
Does the Fed Respond to Oil Price Shocks
A common view in the literature is that systematic monetary policy responses to the inflation caused by oil price shocks have been an important source of aggregate fluctuations in the US economy. Earlier empirical evidence in support of such a link was based on inappropriate econometric models. We show that there is no credible evidence that monetary policy responses to oil price shocks caused large aggregate fluctuations in the 1970s and 1980s o…
Real-Time Forecasts of the Real Price of Oil
We construct a monthly real-time dataset consisting of vintages for 1991.1–2010.12 that is suitable for generating forecasts of the real price of oil from a variety of models. We document that revisions of the data typically represent news, and we introduce backcasting and nowcasting techniques to fill gaps in the real-time data. We show that real-time forecasts of the real price of oil can be more accurate than the no-change forecast at horizons…
Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries
There is a long tradition of using oil prices to forecast U.S. real GDP. It has been suggested that the predictive relationship between the price of oil and one-quarter-ahead U.S. real GDP is nonlinear in that (a) oil price increases matter only to the extent that they exceed the maximum oil price in recent years, and that (b) oil price decreases do not matter at all. We examine, first, whether the evidence of in-sample predictability in support …
The Role of Inventories and Speculative Trading in the Global Market for Crude Oil
We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative …
Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach
The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly forecasts of the price of crude oil for horizons up to 2 years, which are widely used by practitioners. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify. An alternative is the use of real-time econometric oil price forecasting models. We investigate the merits of constructing combinatio…
Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us
It has been 40 years since the oil crisis of 1973/74. This crisis has been one of the defining economic events of the 1970s and has shaped how many economists think about oil price shocks. In recent years, a large literature on the economic determinants of oil price fluctuations has emerged. Drawing on this literature, we first provide an overview of the causes of all major oil price fluctuations between 1973 and 2014. We then discuss why oil pri…
Structural Vector Autoregressive Analysis
Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book …
Does drawing down the US Strategic Petroleum Reserve help stabilize oil prices
We study the effects of releases from the US Strategic Petroleum Reserve (SPR) within the context of fully specified models of the global oil market that explicitly allow for storage demand as well as unanticipated changes in the SPR. We show that historically SPR policy interventions, defined as sequences of exogenous SPR shocks during selected periods, have helped stabilize the price of oil. Their effect on the price of oil, however, has been m…
Oil prices, gasoline prices, and inflation expectations
It has long been suspected, given the salience of gasoline prices, that fluctuations in gasoline prices shift households' 1‐year inflation expectations. Assessing this view empirically requires the use of dynamic structural models to quantify the cumulative effect of gasoline price shocks on household inflation expectations at each point in time. We find that, on average, gasoline price shocks account for 42% of the variation in these expectation…
Macroeconomic Responses to Uncertainty Shocks: The Perils of Recursive Orderings
A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autoregressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of unc…
When Is the Use of Gaussian-Inverse Wishart-Haar Priors Appropriate
Estimating Macroeconomic News and Surprise Shocks
A common VAR approach is to identify responses to TFP news shocks by maximizing the variance share of TFP over a long horizon. We find that these TFP max share estimators tend to be biased in large samples when applied to data generated from DSGE models with shock processes that match TFP moments in the data, especially in the presence of TFP measurement error. We propose an alternative max share news estimator that reduces this bias and the RMSE…
The Conventional Impulse Response Prior in VAR Models With Sign Restrictions
Some studies have expressed concern that the Gaussian‐inverse Wishart–Haar prior typically employed in estimating sign‐identified VAR models may be unintentionally informative about the prior for the structural responses. We discuss what features to look for in this prior in the absence of specific prior information about the responses, building on the notion of weakly informative priors in Gelman et al. (2013), and in the presence of such inform…
Econometrics (17 works) · Market Dynamics and Volatility (17 works) · Economics (16 works) · Monetary Policy and Economic Impact (13 works) · Energy, Environment, and Transportation Policies (12 works) · Mathematics (11 works) · Monetary economics (10 works) · Statistics (10 works) · Oil price (9 works) · Computer Science (8 works)