The paper addresses the problem of "how to make a nonstationary inflation rate stationary by controlling the policy instrument". It shows that a necessary condition is a significant non-zero element in the long-run impact matrix. An application to US data covering the Burns/Miller periods finds a significant, but positive, long-run impact on inflation from a shock to the policy rate. Furthermore, the long-term bond rate was not found to be cointegrated with the policy rate, the treasury bill rate, nor with the inflation rate. Thus, important links were missing and it would not have been able to bring US CPI inflation down in this period by raising the federal funds rate.

The high inflation occurring in the aftermath of the Corona pandemic rekindled an interest in the previous high inflation period of the 70s. Many feared that inflation was finally back again and hoped that central banks would be able to bring inflation down to previously low levels. To address this issue, the paper uses theoretical results on inflation control in Johansen, S. and K. Juselius (2024) to examine the conditions under which a monetary control rule would bring inflation down. Based on two different monetary policy regimes in the USA, one covering the Burns/Miller chairmanship in 1970–1979 and the other the Greenspan chairmanship in 1987-2006, the paper examines inflation control in the two periods. The empirical results provide little support for the widely held belief that the Federal Reserve Bank would have been able to control inflation by raising the federal funds rate. A discussion of why this was the case concludes the paper.

This chapter discusses the CVAR model and how it handles the problem of political reforms, interventions, and structural change at the same time taking account of unit root persistence, strong dynamics, and interactions, all of them dominant features of macroeconomic data. The CVAR describes our complex reality as a system that is driven by 'pulling and pushing forces' which describe the exogenous forces that have pushed the economic system out of equilibrium and the equilibrating forces that have pulled the system back. Being a general-to-specific approach, the CVAR does not from the outset impose untested (theory-consistent) restrictions on the data and, therefore, can represent a whole set of possible economic models. Its usefulness comes from the possibility to test relevant economic hypotheses on the pulling and pushing forces. The economic model that passes such a first check is potentially a candidate for an empirically relevant economic model. The scientific problem is how to associate the concepts of the broader, statistically based, CVAR model to the more narrow concepts of the economic model. A so-called theory-consistent CVAR scenario offers a bridging principle by deriving a set of testable empirical regularities related to the pulling and pushing forces that should be found in the data if the basic assumptions of the economic model are empirically valid. In practice, few economic models have passed this test. The chapter discusses three standard assumptions that seem crucially important for this failure and concludes that a change in research paradigm is much needed.

A theory-consistent CVAR scenario describes a set of testable regularities capturing basic assumptions of the theoretical model. Using this concept, the paper considers a standard model for exchange rate determination with forward-looking expectations and shows that all assumptions about the model’s shock structure and steady-state behavior can be formulated as testable hypotheses on common stochastic trends and cointegration. The basic stationarity assumptions of the monetary model failed to obtain empirical support. They were too restrictive to explain the observed long persistent swings in the real exchange rate, the real interest rates, and the inflation and interest rate differentials.

Understanding changes to the mass of the polar ice sheets is of crucial scientific and socioeconomic importance due to their effect on the wider Earth system and potential to contribute to future sea level rise. On monthly to multi-decadal timescales, there is much uncertainty around the extent to which the non-stationary, non-linear responses of the ice sheets interact through the atmosphere-ocean climate. We test and quantify the nature of non-stationarity and inter-dependence between ice mass balance time series for Greenland, West and East Antarctica using a multi-cointegration vector autoregression model, which has been used to show equivalence between simple climate models and emulations of complex physical processes. We focus on three alternative specifications by comparing I(2) models of cumulative ice mass balance with an I(1) model of the ice mass balance, exploring the model dynamics, and evaluating the out-of-sample forecasts against satellite observations. Our results support the I(2) model with a bipolar relationship between Greenland and West Antarctica and provide some of the first empirical evidence of tipping-points in the recent observed record. Long-term projections indicate that there is considerable risk of Greenland contributing more to sea level rise than under the IPCC's extreme climate change scenario.

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.

Inspired by the paper by , 'Towards a dynamic disequilibrium theory with randomness,' NBER Working Paper 27453), this article shows that cointegrated VAR (CVAR) analyses have for many years provided empirical underpinnings for most of the topics discussed in that paper. The CVAR takes the nonstationarity of economic data seriously; it allows explicitly for complex adjustment dynamics in the short run and the long run; it is able to describe self-reinforcing feedback mechanisms leading to multiple equilibria; it is able to handle extraordinary shocks to the system whether they are exogenously or endogenously induced; and it is able to accommodate sizeable crisis periods such as the Great Recession. The article discusses these issues and many more from a methodological, econometric, and empirical point of view and illustrates the ideas with an application to the Phillips curve with a Phelpsian natural rate based on US data.

<p>The greatest sources of uncertainty for future sea-level rise are the Greenland and Antarctic ice sheets. An important aspect of this uncertainty is the potential interconnectivity between them, which may amplify underlying instabilities in individual ice sheets. We explore these connections empirically by modelling the ice sheets as a cointegrated system. We consider two specications which allow the ice sheets to follow either an I(1) or an I(2) process in order to disentangle the long-run theory consistent relationships in the data. We examine the stability of these relationships over time both in and out of sample and eximine how a sudden loss of ice in Greenland propagates through the system. We show that a 1 Gigatonne loss of ice leads to a large and persistent loss of ice in West Arctica which is partially offset by an accumulation of ice in East Antarctica. Accounting for the long-run interactions between the ice sheets helps to improve our understanding of future instabilities and provides useful projections of the future paths of the ice sheets.</p>

De traditionelle makroøkonomiske modeller bygger på et stort antal teoretiske forudsætninger, som passer dårligt med virkelighedens data. Derfor overser de, at det var dereguleringen af den finansielle sektor, som var den afgørende faktor både for, at gængse økonomiske modeller ikke længere passer, og for at mange ting er gået skævt i vores samfund. Hvis vi ignorerer dette forhold, betyder det, at regnemodellerne i bedste fald kun fanger en begrænset del af, hvad der foregår i den samlede økonomi.

While there seems to be a well-established consensus about the underlying causes to the Greek crisis, less is known about internal and external transmission mechanisms that ultimately caused unemployment to increase rapidly over this period. Motivated by the structural slumps theory in Phelps (Structural slumps, 1994), the paper attempts, therefore, to uncover the dynamic mechanisms behind prices, interest rates, and external imbalances that contributed to the severity and the length of the crisis. The authors find that the strongly increasing real bond rate and unemployment rate together with an persistently appreciating real exchange rate and a deterioration of competitiveness in the eurozone have contributed to persistently growing structural imbalances in the Greek economy. As the lack of confidence in the Greek economy grew steadily, the scene was set for a monumental structural slump. Over the crisis period, all variables exhibited self-reinforcing feedback adjustment somewhere in the system except for inflation rate. Unemployment took the burden of adjustment when the bond rate sky rocketed, competitiveness deteriorated, and confidence fell.

This paper uses consensus forecasts to address empirical puzzles in international macro using the Cointegrated VAR model. The data, consisting of three-month Libor rates, their three-month ahead forecasts, prices and exchange rates for the US and UK, were all found to be near I(2) consistent with imperfect knowledge expectations. The I(2) analysis showed that over the medium run the nominal exchange rate has moved away from equilibrium values with interest rates following suit, whereas over the long run the nominal exchange rate was adjusting while the interest rate forecasts pushed the system away from steady state. Evidence of self-reinforcing feedback mechanisms in the system signals the importance of speculative bubbles for the determination of the exchange rate and the interest rates. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract The cointegrated VAR approach combines differences of variables with cointegration among them and by doing so allows the user to study both long-run and short-run effects in the same model. The CVAR describes an economic system where variables have been pushed away from long-run equilibria by exogenous shocks (the pushing forces) and where short-run adjustments forces pull them back toward long-run equilibria (the pulling forces). In this model framework, basic assumptions underlying a theory model can be translated into testable hypotheses on the order of integration and cointegration of key variables and their relationships. The set of hypotheses describes the empirical regularities we would expect to see in the data if the long-run properties of a theory model are empirically relevant.

As an empirical econometrician, I have always strongly believed in the power of analyzing statistical models as a scientifically viable way of learning from observed data.In the aftermath of the great recession, this seems more important than ever.Most economic and econometric models in macroeconomics and finance did not seem well geared to address features in the data of key importance for this crisis.In particular, the long persistent movements away from long-run equilibrium values typical of the pre-crisis period seem crucial in this respect.Because of this, I hoped that the papers submitted to this Special Issue would use cointegration to address these important issues, for example by applying cointegration to models with self-reinforcing feed-back mechanisms, or by deriving new tests motivated by such empirical applications, or by dealing with near integration in the I(1) and I(2) models.Without a doubt, the outcome has surpassed my most optimistic expectations.This Special Issue contains excellent contributions structured around several interconnected themes, most of them addressing the abovementioned issues in one way or the other.While some of the papers are predominantly theoretical and others are mainly empirical, all of them represent a good mixture of theory and application.The theoretical papers solve problems motivated by empirical work and the empirical papers address problems using valid statistical procedures.In this sense, the collection of articles represents econometric modeling at its best.As the guest editor, I feel both proud and grateful to be presenting an issue containing so many high-quality research papers.The high quality of the articles is to a significant degree a result of detailed, insightful, and very useful referee reports.I would like to take the opportunity to express a deeply felt gratitude to all the reviewers who have invested their precious time to check and improve the quality of the articles.Your efforts made all the difference.

A theory-consistent CVAR scenario describes a set of testable regularieties one should expect to see in the data if the basic assumptions of the theoretical model are empirically valid. Using this method, the paper demonstrates that all basic assumptions about the shock structure and steady-state behavior of an an imperfect knowledge based model for exchange rate determination can be formulated as testable hypotheses on common stochastic trends and cointegration. This model obtaines remarkable support for almost every testable hypothesis and is able to adequately account for the long persistent swings in the real exchange rate.

A theory-consistent CVAR scenario describes a set of testable regularities capturing basic assumptions of the theoretical model. Using this concept, the paper considers a standard model for exchange rate determination and shows that all assumptions about the model?s shock structure and steady-state behavior can be formulated as testable hypotheses on common stochastic trends and cointegration. While the scenario was rejected on essentially all counts, the results were informative about the cause of the empirical failure. It was the stationarity assumptions that were too restrictive to explain the long persistent swings in the real exchange rate and the interest rate differential.

A recent study of 36 sub-Saharan African countries found a positive impact of aid in the majority of these countries. However, for Tanzania and Ghana, two major aid recipients, aid did not seem to have been equally beneficial. This study singles out these two countries for a more detailed empirical investigation. The focus is on the effect of aid when allowing external and nominal factors to play a role in the macroeconomic transmission mechanism. We conclude that when monetary and external factors are properly accounted for, then aid has been pivotal to growth in both real GDP and investment.

Summary The PPP puzzle refers to the wide swings of nominal exchange rates around their long‐run equilibrium values whereas the excess return puzzle represents the persistent deviation of the domestic‐foreign interest rate differential from the expected change in the nominal exchange rate. Using the I (2) cointegrated VAR model, much of the excess return puzzle disappears when an uncertainty premium in the foreign exchange market, proxied by the persistent PPP gap, is introduced. Self‐reinforcing feedback mechanisms seem to cause the persistence in the Swiss‐US parity conditions. These results support imperfect knowledge based expectations rather than so‐called “rational expectations”.

We test competing forms of the Milankovitch hypothesis by estimating the coefficients and diagnostic statistics for a cointegrated vector autoregressive model that includes 10 climate variables and four exogenous variables for solar insolation. The estimates are consistent with the physical mechanisms postulated to drive glacial cycles. They show that the climate variables are driven partly by solar insolation, determining the timing and magnitude of glaciations and terminations, and partly by internal feedback dynamics, pushing the climate variables away from equilibrium. We argue that the latter is consistent with a weak form of the Milankovitch hypothesis and that it should be restated as follows: internal climate dynamics impose perturbations on glacial cycles that are driven by solar insolation. Our results show that these perturbations are likely caused by slow adjustment between land ice volume and solar insolation. The estimated adjustment dynamics show that solar insolation affects an array of climate variables other than ice volume, each at a unique rate. This implies that previous efforts to test the strong form of the Milankovitch hypothesis by examining the relationship between solar insolation and a single climate variable are likely to suffer from omitted variable bias.

The paper provides a careful, analytical account of Trygve Haavelmo's use of the analogy between controlled experiments common in the natural sciences and econometric techniques. The experimental analogy forms the linchpin of the methodology for passive observation that he develops in his famous monograph, The Probability Approach in Econometrics (1944). Contrary to some recent interpretations of Haavelmo's method, the experimental analogy does not commit Haavelmo to a strong apriorism in which econometrics can only test and reject theoretical hypotheses, rather it supports the acquisition of knowledge through a two-way exchange between theory and empirical evidence. Once the details of the analogy are systematically understood, the experimental analogy can be used to shed light on theory-consistent cointegrated vector autoregression (CVAR) scenario analyses. A CVAR scenario analysis can be interpreted as a clear example of Haavelmo's 'experimental' approach; and, in turn, it can be shown to extend and develop Haavelmo's methodology and to address issues that Haavelmo regarded as unresolved.