Econometrics

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4 pages, 196 KiB

Open AccessEditorial

Celebrated Econometricians: Katarina Juselius and Søren Johansen

by Rocco Mosconi and Paolo Paruolo

Econometrics 2022, 10(2), 24; https://doi.org/10.3390/econometrics10020024 - 16 May 2022

Viewed by 2356

Abstract

This Special Issue collects contributions related to the advances in the theory and practice of Econometrics induced by the research of Katarina Juselius and Søren Johansen, whom this Special Issue aims to celebrate [...] Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

16 pages, 1040 KiB

Open AccessEditorial

A Conversation with Søren Johansen

by Rocco Mosconi and Paolo Paruolo

Econometrics 2022, 10(2), 21; https://doi.org/10.3390/econometrics10020021 - 13 Apr 2022

Cited by 1 | Viewed by 3667

Abstract

This article was prepared for the Special Issue “Celebrated Econometricians: Katarina Juselius and Søren Johansen” of Econometrics. It is based on material recorded on 30 October 2018 in Copenhagen. It explores Søren Johansen’s research, and discusses inter alia the following issues: estimation [...] Read more.

This article was prepared for the Special Issue “Celebrated Econometricians: Katarina Juselius and Søren Johansen” of Econometrics. It is based on material recorded on 30 October 2018 in Copenhagen. It explores Søren Johansen’s research, and discusses inter alia the following issues: estimation and inference for nonstationary time series of the I(1), I(2) and fractional cointegration types; survival analysis; statistical modelling; likelihood; econometric methodology; the teaching and practice of Statistics and Econometrics. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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21 pages, 803 KiB

Open AccessEditorial

A Conversation with Katarina Juselius

by Rocco Mosconi and Paolo Paruolo

Econometrics 2022, 10(2), 20; https://doi.org/10.3390/econometrics10020020 - 13 Apr 2022

Cited by 3 | Viewed by 3194

Abstract

This article was prepared for the Special Issue ‘Celebrated Econometricians: Katarina Juselius and Søren Johansen’ of Econometrics. It is based on material recorded on 30–31 October 2018 in Copenhagen. It explores Katarina Juselius’ research, and discusses inter alia the following issues: equilibrium; [...] Read more.

This article was prepared for the Special Issue ‘Celebrated Econometricians: Katarina Juselius and Søren Johansen’ of Econometrics. It is based on material recorded on 30–31 October 2018 in Copenhagen. It explores Katarina Juselius’ research, and discusses inter alia the following issues: equilibrium; short and long-run behaviour; common trends; adjustment; integral and proportional control mechanisms; model building and model comparison; breaks, crisis, learning; univariate versus multivariate modelling; mentoring and the gender gap in Econometrics. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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Research

Jump to: Editorial, Other

27 pages, 469 KiB

Open AccessEditor’s ChoiceArticle

Cointegration, Root Functions and Minimal Bases

by Massimo Franchi and Paolo Paruolo

Econometrics 2021, 9(3), 31; https://doi.org/10.3390/econometrics9030031 - 17 Aug 2021

Cited by 2 | Viewed by 3127

Abstract

This paper discusses the notion of cointegrating space for linear processes integrated of any order. It first shows that the notions of (polynomial) cointegrating vectors and of root functions coincide. Second, it discusses how the cointegrating space can be defined (i) as a [...] Read more.

This paper discusses the notion of cointegrating space for linear processes integrated of any order. It first shows that the notions of (polynomial) cointegrating vectors and of root functions coincide. Second, it discusses how the cointegrating space can be defined (i) as a vector space of polynomial vectors over complex scalars, (ii) as a free module of polynomial vectors over scalar polynomials, or finally (iii) as a vector space of rational vectors over rational scalars. Third, it shows that a canonical set of root functions can be used as a basis of the various notions of cointegrating space. Fourth, it reviews results on how to reduce polynomial bases to minimal order—i.e., minimal bases. The application of these results to Vector AutoRegressive processes integrated of order 2 is found to imply the separation of polynomial cointegrating vectors from non-polynomial ones. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

28 pages, 979 KiB

Open AccessArticle

Søren Johansen and Katarina Juselius: A Bibliometric Analysis of Citations through Multivariate Bass Models

by Fragiskos Archontakis and Rocco Mosconi

Econometrics 2021, 9(3), 30; https://doi.org/10.3390/econometrics9030030 - 12 Aug 2021

Cited by 5 | Viewed by 3734

Abstract

We showcase the impact of Katarina Juselius and Søren Johansen’s contribution to econometrics using bibliometric data on citations from 1989 to 2017, extracted from the Web of Science (WoS) database. Our purpose is to analyze the impact of KJ and SJ’s ideas on [...] Read more.

We showcase the impact of Katarina Juselius and Søren Johansen’s contribution to econometrics using bibliometric data on citations from 1989 to 2017, extracted from the Web of Science (WoS) database. Our purpose is to analyze the impact of KJ and SJ’s ideas on applied and methodological research in econometrics. To this aim, starting from WoS data, we derived two composite indices whose purpose is to disentangle the authors’ impact on applied research from their impact on methodological research. As of 2017, the number of applied citing papers per quarter had not yet reached the peak; conversely, the peak in the methodological literature seem to have been reached around 2000, although the shape of the trajectory is very flat after the peak. We analyzed the data using a multivariate dynamic version of the well known Bass model. Our estimates suggest that the methodological literature is mainly driven by “innovators”, whereas “imitators” are relatively more important in the applied literature: this might explain the different location of the peaks. We also find that, in the literature referring to KJ and SJ, the “cross-fertilization” between methodological and applied research is statistically significant and bi-directional. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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27 pages, 377 KiB

Open AccessFeature PaperArticle

Searching for a Theory That Fits the Data: A Personal Research Odyssey

by Katarina Juselius

Econometrics 2021, 9(1), 5; https://doi.org/10.3390/econometrics9010005 - 1 Feb 2021

Cited by 9 | Viewed by 4306

Abstract

This survey paper discusses the Cointegrated Vector AutoRegressive (CVAR) methodology and how it has evolved over the past 30 years. It describes major steps in the econometric development, discusses problems to be solved when confronting theory with the data, and, as a solution, [...] Read more.

This survey paper discusses the Cointegrated Vector AutoRegressive (CVAR) methodology and how it has evolved over the past 30 years. It describes major steps in the econometric development, discusses problems to be solved when confronting theory with the data, and, as a solution, proposes a so-called theory-consistent CVAR scenario. A number of early CVAR applications are motivated by the urge to find out why the empirical results did not support Milton Friedman’s concept of monetary inflation. The paper also proposes a method for combining partial CVAR analyses into a large-scale macroeconomic model. It argues that an empirically-based approach to macroeconomics preferably should be based on Keynesian disequilibrium economics, where imperfect knowledge expectations replace so called rational expectations and where the financial sector plays a key role for understanding the long persistent movements in the data. Finally, the paper argues that the CVAR is potentially a candidate for Haavelmo’s “design of experiment for passive observations” and provides several illustrations. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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26 pages, 350 KiB

Open AccessArticle

Forward Rate Bias in Developed and Developing Countries: More Risky Not Less Rational

by Michael D. Goldberg, Olesia Kozlova and Deniz Ozabaci

Econometrics 2020, 8(4), 43; https://doi.org/10.3390/econometrics8040043 - 2 Dec 2020

Cited by 1 | Viewed by 3569

Abstract

This paper examines the stability of the Bilson–Fama regression for a panel of 55 developed and developing countries. We find multiple break points for nearly every country in our panel. Subperiod estimates of the slope coefficient show a negative bias during some time [...] Read more.

This paper examines the stability of the Bilson–Fama regression for a panel of 55 developed and developing countries. We find multiple break points for nearly every country in our panel. Subperiod estimates of the slope coefficient show a negative bias during some time periods and a positive bias during other time periods in nearly every country. The subperiod biases display two key patterns that shed light on the literature’s linear regression findings. The results point toward the importance of risk in currency markets. We find that risk is greater for developed country markets. The evidence undercuts the widespread view that currency returns are predictable or that developed country markets are less rational. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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54 pages, 640 KiB

Open AccessArticle

A Parameterization of Models for Unit Root Processes: Structure Theory and Hypothesis Testing

by Dietmar Bauer, Lukas Matuschek, Patrick de Matos Ribeiro and Martin Wagner

Econometrics 2020, 8(4), 42; https://doi.org/10.3390/econometrics8040042 - 10 Nov 2020

Cited by 3 | Viewed by 3247

Abstract

We develop and discuss a parameterization of vector autoregressive moving average processes with arbitrary unit roots and (co)integration orders. The detailed analysis of the topological properties of the parameterization—based on the state space canonical form of Bauer and Wagner (2012)—is an essential input [...] Read more.

We develop and discuss a parameterization of vector autoregressive moving average processes with arbitrary unit roots and (co)integration orders. The detailed analysis of the topological properties of the parameterization—based on the state space canonical form of Bauer and Wagner (2012)—is an essential input for establishing statistical and numerical properties of pseudo maximum likelihood estimators as well as, e.g., pseudo likelihood ratio tests based on them. The general results are exemplified in detail for the empirically most relevant cases, the (multiple frequency or seasonal) I(1) and the I(2) case. For these two cases we also discuss the modeling of deterministic components in detail. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

28 pages, 437 KiB

Open AccessArticle

Modeling I(2) Processes Using Vector Autoregressions Where the Lag Length Increases with the Sample Size

by Yuanyuan Li and Dietmar Bauer

Econometrics 2020, 8(3), 38; https://doi.org/10.3390/econometrics8030038 - 17 Sep 2020

Cited by 4 | Viewed by 3611

Abstract

In this paper the theory on the estimation of vector autoregressive (VAR) models for I(2) processes is extended to the case of long VAR approximation of more general processes. Hereby the order of the autoregression is allowed to tend to infinity at a [...] Read more.

In this paper the theory on the estimation of vector autoregressive (VAR) models for I(2) processes is extended to the case of long VAR approximation of more general processes. Hereby the order of the autoregression is allowed to tend to infinity at a certain rate depending on the sample size. We deal with unrestricted OLS estimators (in the model formulated in levels as well as in vector error correction form) as well as with two stage estimation (2SI2) in the vector error correction model (VECM) formulation. Our main results are analogous to the I(1) case: We show that the long VAR approximation leads to consistent estimates of the long and short run dynamics. Furthermore, tests on the autoregressive coefficients follow standard asymptotics. The pseudo likelihood ratio tests on the cointegrating ranks (using the Gaussian likelihood) used in the 2SI2 algorithm show under the null hypothesis the same distributions as in the case of data generating processes following finite order VARs. The same holds true for the asymptotic distribution of the long run dynamics both in the unrestricted VECM estimation and the reduced rank regression in the 2SI2 algorithm. Building on these results we show that if the data is generated by an invertible VARMA process, the VAR approximation can be used in order to derive a consistent initial estimator for subsequent pseudo likelihood optimization in the VARMA model. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

25 pages, 1708 KiB

Open AccessFeature PaperArticle

The Discovery of Long-Run Causal Order: A Preliminary Investigation

by Kevin D. Hoover

Econometrics 2020, 8(3), 31; https://doi.org/10.3390/econometrics8030031 - 3 Aug 2020

Cited by 8 | Viewed by 4429

Abstract

The relation between causal structure and cointegration and long-run weak exogeneity is explored using some ideas drawn from the literature on graphical causal modeling. It is assumed that the fundamental source of trending behavior is transmitted from exogenous (and typically latent) trending variables [...] Read more.

The relation between causal structure and cointegration and long-run weak exogeneity is explored using some ideas drawn from the literature on graphical causal modeling. It is assumed that the fundamental source of trending behavior is transmitted from exogenous (and typically latent) trending variables to a set of causally ordered variables that would not themselves display nonstationary behavior if the nonstationary exogenous causes were absent. The possibility of inferring the long-run causal structure among a set of time-series variables from an exhaustive examination of weak exogeneity in irreducibly cointegrated subsets of variables is explored and illustrated. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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15 pages, 301 KiB

Open AccessArticle

Cointegration and Structure in Norwegian Wage–Price Dynamics

by Marit Gjelsvik, Ragnar Nymoen and Victoria Sparrman

Econometrics 2020, 8(3), 29; https://doi.org/10.3390/econometrics8030029 - 27 Jul 2020

Cited by 6 | Viewed by 5667

Abstract

Wage coordination plays an important role in macroeconomic stabilization. Pattern wage bargaining systems have been common in Europe, but in different forms, and with different degrees of success in terms of actual coordination reached. We focus on wage formation in Norway, a small [...] Read more.

Wage coordination plays an important role in macroeconomic stabilization. Pattern wage bargaining systems have been common in Europe, but in different forms, and with different degrees of success in terms of actual coordination reached. We focus on wage formation in Norway, a small open economy, where it is custom to regard the manufacturing industry as the wage leader. We estimate a model of wage formation in manufacturing and in two other sectors. Deciding cointegration rank is an important step in the analysis, economically as well statistically. In combination with simultaneous equation modelling, the cointegration analysis provides evidence that collective wage negotiations in manufacturing have defined wage norms for the rest of the economy over the period 1980(1)–2014(4). Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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23 pages, 361 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors

by Matteo Barigozzi, Marco Lippi and Matteo Luciani

Econometrics 2020, 8(1), 3; https://doi.org/10.3390/econometrics8010003 - 4 Feb 2020

Cited by 14 | Viewed by 6116

Abstract

Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with

q < r

. The present paper [...] Read more.

Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with

q < r

. The present paper studies cointegration and error correction representations for an

I (1)

singular stochastic vector

y_{t}

. It is easily seen that

y_{t}

is necessarily cointegrated with cointegrating rank

c \geq r - q

. Our contributions are: (i) we generalize Johansen’s proof of the Granger representation theorem to

I (1)

singular vectors under the assumption that

y_{t}

has rational spectral density; (ii) using recent results on singular vectors by Anderson and Deistler, we prove that for generic values of the parameters the autoregressive representation of

y_{t}

has a finite-degree polynomial. The relationship between the cointegration of the factors and the cointegration of the observable variables in a large-dimensional factor model is also discussed. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

35 pages, 584 KiB

Open AccessArticle

Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms

by Takamitsu Kurita and Bent Nielsen

Econometrics 2019, 7(4), 42; https://doi.org/10.3390/econometrics7040042 - 6 Oct 2019

Cited by 8 | Viewed by 5741

Abstract

This paper proposes a class of partial cointegrated models allowing for structural breaks in the deterministic terms. Moving-average representations of the models are given. It is then shown that, under the assumption of martingale difference innovations, the limit distributions of partial quasi-likelihood ratio [...] Read more.

This paper proposes a class of partial cointegrated models allowing for structural breaks in the deterministic terms. Moving-average representations of the models are given. It is then shown that, under the assumption of martingale difference innovations, the limit distributions of partial quasi-likelihood ratio tests for cointegrating rank have a close connection to those for standard full models. This connection facilitates a response surface analysis that is required to extract critical information about moments from large-scale simulation studies. An empirical illustration of the proposed methodology is also provided. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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22 pages, 547 KiB

Open AccessArticle

A Parametric Factor Model of the Term Structure of Mortality

by Niels Haldrup and Carsten P. T. Rosenskjold

Econometrics 2019, 7(1), 9; https://doi.org/10.3390/econometrics7010009 - 11 Mar 2019

Cited by 6 | Viewed by 7453

Abstract

The prototypical Lee–Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper, we propose a parametric factor model for the term structure of mortality where multiple factors are designed to influence the age [...] Read more.

The prototypical Lee–Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper, we propose a parametric factor model for the term structure of mortality where multiple factors are designed to influence the age groups differently via parametric loading functions. We identify four different factors: a factor common for all age groups, factors for infant and adult mortality, and a factor for the “accident hump” that primarily affects mortality of relatively young adults and late teenagers. Since the factors are identified via restrictions on the loading functions, the factors are not designed to be orthogonal but can be dependent and can possibly cointegrate when the factors have unit roots. We suggest two estimation procedures similar to the estimation of the dynamic Nelson–Siegel term structure model. First, a two-step nonlinear least squares procedure based on cross-section regressions together with a separate model to estimate the dynamics of the factors. Second, we suggest a fully specified model estimated by maximum likelihood via the Kalman filter recursions after the model is put on state space form. We demonstrate the methodology for US and French mortality data. We find that the model provides a good fit of the relevant factors and, in a forecast comparison with a range of benchmark models, it is found that, especially for longer horizons, variants of the parametric factor model have excellent forecast performance. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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24 pages, 391 KiB

Open AccessArticle

Asymptotic Theory for Cointegration Analysis When the Cointegration Rank Is Deficient

by David H. Bernstein and Bent Nielsen

Econometrics 2019, 7(1), 6; https://doi.org/10.3390/econometrics7010006 - 18 Jan 2019

Cited by 5 | Viewed by 9524

Abstract

We consider cointegration tests in the situation where the cointegration rank is deficient. This situation is of interest in finite sample analysis and in relation to recent work on identification robust cointegration inference. We derive asymptotic theory for tests for cointegration rank and [...] Read more.

We consider cointegration tests in the situation where the cointegration rank is deficient. This situation is of interest in finite sample analysis and in relation to recent work on identification robust cointegration inference. We derive asymptotic theory for tests for cointegration rank and for hypotheses on the cointegrating vectors. The limiting distributions are tabulated. An application to US treasury yields series is given. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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10 pages, 254 KiB

Open AccessArticle

Cointegration and Adjustment in the CVAR(∞) Representation of Some Partially Observed CVAR(1) Models

by Søren Johansen

Econometrics 2019, 7(1), 2; https://doi.org/10.3390/econometrics7010002 - 10 Jan 2019

Cited by 5 | Viewed by 6631

Abstract

A multivariate CVAR(1) model for some observed variables and some unobserved variables is analysed using its infinite order CVAR representation of the observations. Cointegration and adjustment coefficients in the infinite order CVAR are found as functions of the parameters in the CVAR(1) model. [...] Read more.

A multivariate CVAR(1) model for some observed variables and some unobserved variables is analysed using its infinite order CVAR representation of the observations. Cointegration and adjustment coefficients in the infinite order CVAR are found as functions of the parameters in the CVAR(1) model. Conditions for weak exogeneity for the cointegrating vectors in the approximating finite order CVAR are derived. The results are illustrated by two simple examples of relevance for modelling causal graphs. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

33 pages, 1056 KiB

Open AccessArticle

The Stochastic Stationary Root Model

by Andreas Hetland

Econometrics 2018, 6(3), 39; https://doi.org/10.3390/econometrics6030039 - 21 Aug 2018

Cited by 1 | Viewed by 7322

Abstract

We propose and study the stochastic stationary root model. The model resembles the cointegrated VAR model but is novel in that: (i) the stationary relations follow a random coefficient autoregressive process, i.e., exhibhits heavy-tailed dynamics, and (ii) the system is observed with measurement [...] Read more.

We propose and study the stochastic stationary root model. The model resembles the cointegrated VAR model but is novel in that: (i) the stationary relations follow a random coefficient autoregressive process, i.e., exhibhits heavy-tailed dynamics, and (ii) the system is observed with measurement error. Unlike the cointegrated VAR model, estimation and inference for the SSR model is complicated by a lack of closed-form expressions for the likelihood function and its derivatives. To overcome this, we introduce particle filter-based approximations of the log-likelihood function, sample score, and observed Information matrix. These enable us to approximate the ML estimator via stochastic approximation and to conduct inference via the approximated observed Information matrix. We conjecture the asymptotic properties of the ML estimator and conduct a simulation study to investigate the validity of the conjecture. Model diagnostics to assess model fit are considered. Finally, we present an empirical application to the 10-year government bond rates in Germany and Greece during the period from January 1999 to February 2018. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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14 pages, 295 KiB

Open AccessArticle

The Relation between Monetary Policy and the Stock Market in Europe

by Helmut Lütkepohl and Aleksei Netšunajev

Econometrics 2018, 6(3), 36; https://doi.org/10.3390/econometrics6030036 - 5 Aug 2018

Cited by 14 | Viewed by 9729

Abstract

We use a cointegrated structural vector autoregressive model to investigate the relation between monetary policy in the euro area and the stock market. Since there may be an instantaneous causal relation, we consider long-run identifying restrictions for the structural shocks and also used [...] Read more.

We use a cointegrated structural vector autoregressive model to investigate the relation between monetary policy in the euro area and the stock market. Since there may be an instantaneous causal relation, we consider long-run identifying restrictions for the structural shocks and also used (conditional) heteroscedasticity in the residuals for identification purposes. Heteroscedasticity is modelled by a Markov-switching mechanism. We find a plausible identification scheme for stock market and monetary policy shocks which is consistent with the second-order moment structure of the variables. The model indicates that contractionary monetary policy shocks lead to a long-lasting downturn of real stock prices. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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9 pages, 225 KiB

Open AccessArticle

Johansen’s Reduced Rank Estimator Is GMM

by Bruce E. Hansen

Econometrics 2018, 6(2), 26; https://doi.org/10.3390/econometrics6020026 - 18 May 2018

Cited by 11 | Viewed by 8943

Abstract

The generalized method of moments (GMM) estimator of the reduced-rank regression model is derived under the assumption of conditional homoscedasticity. It is shown that this GMM estimator is algebraically identical to the maximum likelihood estimator under normality developed by Johansen (1988). This includes [...] Read more.

The generalized method of moments (GMM) estimator of the reduced-rank regression model is derived under the assumption of conditional homoscedasticity. It is shown that this GMM estimator is algebraically identical to the maximum likelihood estimator under normality developed by Johansen (1988). This includes the vector error correction model (VECM) of Engle and Granger. It is also shown that GMM tests for reduced rank (cointegration) are algebraically similar to the Gaussian likelihood ratio tests. This shows that normality is not necessary to motivate these estimators and tests. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

511 KiB

Open AccessFeature PaperArticle

Evaluating Forecasts, Narratives and Policy Using a Test of Invariance

by Jennifer L. Castle, David F. Hendry and Andrew B. Martinez

Econometrics 2017, 5(3), 39; https://doi.org/10.3390/econometrics5030039 - 1 Sep 2017

Cited by 19 | Viewed by 9242

Abstract

Economic policy agencies produce forecasts with accompanying narratives, and base policy changes on the resulting anticipated developments in the target variables. Systematic forecast failure, defined as large, persistent deviations of the outturns from the numerical forecasts, can make the associated narrative false, which [...] Read more.

Economic policy agencies produce forecasts with accompanying narratives, and base policy changes on the resulting anticipated developments in the target variables. Systematic forecast failure, defined as large, persistent deviations of the outturns from the numerical forecasts, can make the associated narrative false, which would in turn question the validity of the entailed policy implementation. We establish when systematic forecast failure entails failure of the accompanying narrative, which we call forediction failure, and when that in turn implies policy invalidity. Most policy regime changes involve location shifts, which can induce forediction failure unless the policy variable is super exogenous in the policy model. We propose a step-indicator saturation test to check in advance for invariance to policy changes. Systematic forecast failure, or a lack of invariance, previously justified by narratives reveals such stories to be economic fiction. Full article

(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)

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