To Örebro University

This paper investigates the sensitivity of Colombian GDP growth to the surrounding macroeconomic environment. We estimate a Bayesian VAR model with informative steady-state priors for the Colombian economy using quarterly data from 1995 to 2007. A variance decomposition shows that world GDP growth and government spending are the most important factors, explaining roughly 17 and 16 per cent of the variance in Colombian GDP growth respectively. The model, which is shown to forecast well out-of-sample, can also be used to analyse alternative scenarios. Generating both endogenous and conditional forecasts, we show that the impact on Colombian GDP growth of a substantial downturn in world GDP growth would be non-negligible but that the decline still would be mild by historical standards.

This paper assesses the usefulness of constant gain least squares when forecasting inflation.An out-of-sample forecast exercise is conducted, in which univariate autoregressive models for inflation in Australia, Sweden, the United Kingdom and the United States are used. The results suggest that it is possible to improve the forecast accuracy by employing constant gain least squares instead of ordinary least squares. In particular, when using a gain of 0.05, constant gain least squares generally outperforms the corresponding autoregressive model estimated with ordinary least squares. In fact, at longer forecast horizons, the root mean square forecast error is reliably lowered for all four countries and for all lag lengths considered in the study.

In this paper, we assess the usefulness of constant gain least squares (CGLS) when forecasting the unemployment rate. Using quarterly data from 1970 to 2009, we conduct an out-of-sample forecast exercise in which univariate autoregressive models for the unemployment rate in Australia, Sweden, the United Kingdom and the United States are employed. Results show that CGLS very rarely outperforms OLS. At horizons of six to eight quarters, OLS is always associated with higher forecast precision, regardless of model size or gain employed for Australia, Sweden and the United States. Our findings suggest that while CGLS has been shown valuable when forecasting certain macroeconomic time series, it has shortcomings when forecasting the unemployment rate. One problematic feature is found to be an increased tendency for the autoregressive model to have explosive dynamics when estimated with CGLS.

In this paper, the natural rate of interest in Denmark, Norway and Sweden is estimated. This is done by augmenting the Laubach and Williams (Rev Econ Stat 85:1063-1070, 2003) framework with a dynamic factor model linked to economic indicators--a modelling choice which allows us to better identify business cycle fluctuations. We estimate the model using Bayesian methods on data ranging from 1990Q1 to 2022Q4. The results indicate that the natural rate has declined substantially and in all countries is at a low level at the end of the sample.

In this paper, we investigate whether the two main consumer confidence indicators available for Sweden – that of the National Institute of Economic Research and that of the European Commission – can nowcast Swedish household consumption expenditure. In a simulated out-of-sample nowcast exercise, we find that the consumer confidence indicator of the National Institute of Economic Research appears most useful for this purpose. The root mean square error of the nowcast from the model employing this indicator is the lowest of all models relying on survey data. The nowcasting performance of the model using the consumer confidence indicator of the European Commission is less impressive; while it outperforms the simplest possible benchmark model, its root mean square error is considerably higher than that of the model relying on the consumer confidence indicator of the National Institute of Economic Research. An implication of our findings is that while the European Commission’s survey programme may have been successful in creating a set of harmonised data for the member countries of the European Union, it is not obvious that the harmonised indicators are the most relevant ones for analysis, nowcasting or forecasting in each country.

Nominal interest rates are unlikely to be generated by unit-root processes. Using data on short and  long interest rates from eight developed and six emerging economies, we test the expectations hypothesis using cointegration methods under the assumption that interest rates are near integrated. If the null hypothesis of no cointegration is rejected, we then test whether the estimated cointegrating vector is consistent with that suggested by the expectations hypothesis. The results show support for cointegration in 10 of the 14 countries we consider, and the cointegrating vector is similar across countries. However, the parameters differ from those suggested by theory. We relate our findings to existing literature on the failure of the expectations hypothesis and to the role of term premia.

In recent years, the central banks of Norway and Sweden have published their endogenous policy interest‐rate forecasts. In this paper, we evaluate those forecasts alongside policy‐rate expectations inferred from market pricing. We find that for both economies, there are only small differences in relative forecasting precision between the central bank and market‐implied measures. However, both types of forecast fail tests for unbiasedness and efficiency at longer horizons.

Inflation targeting as a monetary-policy regime is widely associated with an explicit numerical target for the rate of inflation. This paper investigates whether the forecasting performance of Bayesian autoregressive models can be improved by incorporating information about the target. We compare a mean-adjusted specification, which allows an informative prior on the distribution for the steady state of the process, to traditional methodology. We find that the out-of-sample forecasts of the mean-adjusted autoregressive model outperform those of the traditional specification, often by non-trivial amounts, for five early adopters of inflation targeting. It is also noted that as the sample lengthens, the posterior distribution of steady-state inflation narrows more for countries with explicit point targets.

In this article, we evaluate two types of Swedish policy interest-rate expectations: survey expectations and expectations inferred from market pricing. The data are drawn from the most prominent survey of financial-market economists and from Swedish financial markets, and they are carefully matched by date to ensure comparability. Results show that both kinds of expectations suffer from bias and inefficiency, and in terms of forecast precision there is no clear winner. We do find, though, evidence that the forecast accuracy of both kinds of policy-rate expectations has improved since the Riksbank started publishing its own policyrate forecast, suggesting that this communication strategy has been beneficial from a policy perspective.

We test for the presence of a unit root in U.S. GDP and CPI, allowing for non-linear trend reversion under the alternative hypothesis. In contrast to most previous results, we find evidence in favour of trend stationarity for both variables.

We estimate the path of inflation persistence in the United States over the last 50 years using an ARMA model of inflation with time-varying autoregressive parameter. The model is motivated by the familiar New-Keynesian framework which, paired with a common model of monetary-policy optimization, predicts that the central bank’s relative preference for output stability is a determinant of inflation persistence. As such, time variation of the relative preference for output stability can generate time-varying inflation persistence. The estimated ARMA model provides an estimate of the inflation objective and the path of inflation persistence. The estimated path of inflation persistence is consistent with a general reading of Federal Reserve history; inflation persistence is estimated to have declined substantially during Volcker and Greenspan’s tenures from the high persistence of the 1970s. Interpreted in light of the theoretical framework, the results suggest that the Federal Reserve has placed increasing weight on inflation stability in recent decades.

This paper investigates how inflation persistence in the Euro area has evolved between 1991 and 2006. Employing an ARMA(1,11) model with time-varying autoregressive parameter, we find that inflation persistence has fallen markedly since the third stage of the EMU began in January 1999 and inflation no longer exhibits unit-root behaviour.

We estimate the trend short-term interest rate in the United States using an unobserved-components stochastic-volatility model with interest-rate and survey data from 1998Q2 to 2022Q4. Our results indicate that the trend short-term interest rate has drifted down during most of the sample and remains low in a historical perspective, despite the recent sharp increase in the short-term interest rate.

We assess the bivariate relation between money growth and inflation in the euro area and the United States using hybrid time-varying parameter Bayesian VAR models. Model selection based on marginal likelihoods suggests that the relation is statistically unstable across time in both regions. The effect of money growth on inflation weakened notably after the 1980s before strengthening after 2020. There is evidence that this time variation is related to the pace of price changes, as we find that the maximum impact of money growth on inflation is increasing in the trend level of inflation. These results caution against asserting a simple, time-invariant relationship when modeling the joint dynamics of monetary aggregates and consumer prices.

We use Bayesian estimation techniques to assess whether money growth Grangercauses inflation in the USA. We investigate the issue of Granger-causality out-of-sample and find that including money growth in simple VAR models of inflation does systematically improve out-of-sample forecasting accuracy. This holds for a long forecasting sample 1960–2005, as well for more recent subperiods, including the Volcker and Greenspan eras. However, the contribution of money to inflation forecasting accuracy is quantitatively limited and tends to be close to negligible in recent subperiods.

We use Bayesian estimation techniques to assess whether money growth Granger causes inflation in the USA. We investigate the issue of Granger-causality out-of-sample and find that including money growth in simple VAR models of inflation does systematically improve out-of-sample forecasting accuracy. This holds for a long forecasting sample 1960–2005, as well for more recent subperiods, including the Volcker and Greenspan eras. However, the contribution of money to inflation forecasting accuracy is quantitatively limited and tends to be close to negligible in recent subperiods.

In this note, we use an out-of-sample approach to investigate whether money growth Granger-causes output growth in the United States. We find that after the ‘Great moderation,’ the Granger-causal role of money appears to have vanished completely.

Survey data from businesses and households are widely used for forecasting and economic analysis. In Sweden, the most important survey of this kind is the Economic Tendency Survey of the National Institute of Economic Research. A shortcoming with this survey is that real-time data of it largely are unavailable. In this paper, we describe how two quasi-real-time data sets of this survey have been constructed – one monthly and one quarterly. The term “quasi-real-time data” refers to data which are not actual real-time data but have been created in order to provide a close approximation to real-time data. The data sets consist of monthly/quarterly vintages of the most important series of the survey, including the main confidence indicators. A natural usage of these data sets is evaluations of model-based forecasts and nowcasts. We illustrate this with an application to Swedish GDP growth. This shows that several of the studied indicators from the Economic Tendency Survey appear to have positive nowcast content for GDP growth.

Much of the information communicated by central banks is noisy or imperfect. This paper considers the potential benefits and limitations of central bank communications in a model of imperfect knowledge and learning. It is shown that the value of communicating imperfect information is ambiguous. If the public is able to assess accurately the quality of the imperfect information communicated by a central bank, such communication can inform and improve the public’s decisions and expectations. But if not, communicating imperfect information has the potential to mislead and distract. The risk that imperfect communication may detract from the public’s understanding should be considered in the context of a central bank’s communications strategy. The risk of distraction means the central bank may prefer to focus its communication policies on the information it knows most about. Indeed, conveying more certain information may improve the public’s understanding to the extent that it “crowds out” a role for communicating imperfect information.

I denna artikel analyseras inflations- och löneförväntningarna i Prospera-enkäten ur ett prognosperspektiv. Resultaten indikerar att alla grupper i enkäten förefaller att på samtliga prognoshorisonter systematiskt ha överskattat inflationsutfallen. Löneförväntningarna verkar å andra sidan i viss utsträckning ha underskattat utfallen i lönetillväxt, åtminstone på den kortaste prognoshorisonten. Det finns även indikationer på att såväl inflations- som löneförväntningarna inte är effektiva ur ett prognoshänseende. Sammantaget förefaller det som om förväntningarna i Prospera-enkäten har vissa brister rörande väntevärdesriktighet och prognoseffektivitet. Beträffande prognosprecision kan det noteras att penningmarknadsaktörerna är den mest träffsäkra gruppen när det gäller inflationsförväntningarna medan arbetstagarorganisationerna har högst prognosprecision på ett- och tvåårshorisonten rörande löneförväntningarna.

In this paper, we study revisions of Swedish national accounts data. Three aspects of the revisions are considered: volatility, unbiasedness and forecast efficiency. Our results indicate that the properties of the revisions are more problematic for the production side than for the expenditure side. The high volatility of the revisions on the production side indicates that it is generally difficult to make clear cut statements concerning production across industries within the business sector based on the initial data release; it is also likely to make forecasting more difficult.

Real housing prices in Sweden have roughly doubled the last 15 years. The rise in housing prices has coincided with a rise in household debt, sparking debate about both the presence of financial imbalances in the Swedish economy and the macroeconomic effects that a correction of these imbalances would have. In this paper, we conduct a quantitative assessment of the macroeconomic effects of a considerable decline inhousing prices using a Bayesian VAR model. Results show that a 20% drop in housing prices would lead to a recession-like impact on household consumption and unemployment. The impact would be even greater if falling housing prices coincided with a global economic downturn. This information should be useful to policymakers. If a fall in housing prices were to materialize, more expansionary stabilization policies would be motivated in order to dampen the effects on the real economy.

Calibrations of models related to life-cycle behavior of consumption and saving often invoke the important assumption of a unit root in individuals' labor-income process. We for the first time test this assumption using methods for univariate time series. Based on longitudinal register data from 1968 to 2005, we first estimate an autoregressive model for each individual using a method for approximately median-unbiased estimation. We then exploit the resulting distribution of the individual-specific estimates to draw inference about the presence of a unit root. Results indicate that earnings for the representative worker are governed by a process where shocks to earnings have moderate persistence and are both economically and statistically significantly different from having permanent effects. These results question the heavy use of unit-root processes for earnings.

The informational value of the aggregate US unemployment rate has recently been questioned because of a unit root in the labor-force participation rate; the lack of mean reversion implies that long-run changes in unemployment rates are highly unlikely to reflect long-run changes in joblessness. This note shows that this critique also extends to unemployment rates for sub-populations, such as prime-aged males.

Using a battery of unit root tests, we show that labor force participation rates in Australia, Canada and the U.S. are non-stationary. This implies that great care is needed before unemployment rates are used as measures of joblessness.

This paper investigates the relevance of unemployment hysteresis in seventeen OECD countries. We employ an out-of-sample forecast exercise in which a mean-reverting autoregressive model is compared to an autoregressive model with an imposed unit root. A substantial difference in forecasting performance between the twomodels is established formany countries, but the results aremixed in their strength. The evidence for unemployment hysteresis in Austria, Finland, Iceland, Israel, Italy, Japan and Sweden is, however, convincing. For no country can unambiguous support for a mean reverting unemployment rate be found.

We analyse micro-level survey data, ranging from 2010 to 2017, on Swedish households' mortgage-rate expectations. Our key finding is that expectations at the longest horizon are significantly related to age, where the youngest age group has the lowest expectations.

We assess whether the concept of anchoring – where a respondent’s answer is affected by the reference number stated in the survey question – is related to the characteristics of the respondent. Using a survey of household expectations of Swedish housing prices, we find significant differences in observed anchoring across groups reflecting age, income, homeownership and sex. Implications for the interpretation of survey results are discussed.

Expectations about future housing prices are arguably an important determinant of actual housing prices, and an important input in decisions on whether and how to transact in the housing market. Using micro-level survey data on Swedish households, we analyse households’ expectations of housing prices and how these expectations relate to the characteristics of the respondents. Results show that age is found to be significantly related to housing-price expectations, with the youngest households – whose adulthood largely corresponds to the extended period of rapid housing-price growth in Sweden – having the highest housing-price expectations. This is consistent with the hypothesis that expectations are influenced by personal experiences. Our findings suggest that aggregate measures of expectations might hide important features of the data, which could be of interest to policy makers when choosing regulatory actions or formulating macroprudential policies.

Household expectations of future mortgage rates elicited over the last few years might appear unrealistically low. However, taking explicit account of the high persistence in interest rates, we find that Swedish households’ implied longterm expectation of mortgage rates is around 4.7 per cent. This number lines up well with the long-term expectation that can be deduced from the Riksbank’s assessment of the repo rate in the long run and the typical spread between the mortgage rate and the repo rate. Our analysis makes use of household mortgage-rate expectations at three different horizons, which enables an explicit modelling of the ‘term-structure’ of household forecasts.

I denna artikel analyseras hur svenska hushålls förväntningar rörande bolåneränta och bostadspriser förhåller sig till olika egenskaper hos respondenten. Resultaten tyder på att det finns väsentlig heterogenitet i förväntningar mellan respondentgrupper. Ett resultat som är särskilt intressant är att de yngsta respondenterna tenderar att ha haft de lägsta bolåneränteförväntningarna och de högsta bostadsprisförväntningarna; detta är konsistent med en teoribildning som säger att förväntningar påverkas av våra erfarenheter. Sammantaget indikerar våra resultat bl a att aggregerade måttöver hushållens förväntningar – såsom ett medelvärde taget över alla respondenter – kan dölja relevant heterogenitet som ekonomisk-politiska beslutsfattare kan vara intresserade av.

We investigate the properties of Johansen’s (J Econ Dyn Control 12:231–254, 1988; Econometrica 59:1551–1580, 1991) maximum eigenvalue and trace testsfor cointegration under the empirically relevant situation of near-integrated variables. Using MonteCarlo techniques, we showthat in a systemwith near-integrated variables, the probability of reaching an erroneous conclusion regarding the cointegrating rank of the system is generally substantially higher than the nominal size. The risk of concluding that completely unrelated series are cointegrated is therefore non-negligible. We suggest ways of identifying the problem and different approaches to reduce the size distortions of the tests.

The nowcasting performance of autoregressive models for GDP growth are analysed in a setting where the error term is allowed to be characterized both by conditional heteroscedasticity and non-Gaussianity. Standard, publicly available, quarterly data on GDP growth from 1979 to 2019 for six countries are employed: Australia, Canada, France, Japan, the United Kingdom and the United States. In-sample analysis suggests that when homoscedasticity is assumed, support is provided for non-Gaussian error terms; the estimated degrees of freedom of the t-distribution lie between two and seven for all countries. However, allowing for both conditional heteroscedasticity and t-distributed innovations, results indicate that conditional heteroscedasticity captures the fat-tailed behaviour of the data to a large extent. Results from out-of-sample analysis show that point nowcasts are hardly affected by taking conditional heteroscedasticity and/or non-Gaussianity into account. For the density nowcasts, it is found that accounting for conditional heteroscedasticity leads to improvements for Australia, Canada, Japan, the United Kingdom and the United States; allowing for non-Gaussianity seems less important though. This result is robust to which measure is used for assessing density nowcasting performance.

Weevaluate survey-based wage-growth expectations and find that they are neither unbiased nor efficient forecasts. Concerning out-of-sample forecast precision, survey participants generally perform worse than a constant forecast. Caution should accordingly be exercised when relying on these data for policymaking.

This article assesses the properties of survey-based inflation expectations in Sweden. The survey in question is conducted by Prospera once every quarter andconsists of respondents from businesses and labour-market organisations. The article shows that inflation expectations measured in this survey tend to be biased and inefficient forecasts of future inflation. Moreover, evaluations of forecast accuracy show that these inflation expectations are worse predictors of inflation than those of a professional forecasting institution and also typically outperformed by a simple autoregressive model. Given that the true inflation expectations are captured by the survey, our results indicate that economic agents’ expectations formation process is suboptimal.

Att de störningar som drabbar makroekonomin är normalfördelade och har konstant varians är två antaganden som allt oftare har övergivits i den inter-nationella forskningslitteraturen under de senaste två decennierna. I denna artikel undersöks om detta är relevant för ett antal nyckelvariabler i svensk mak-roekonomi. Sammantaget tyder våra resultat på att forskare och policyekonomer som modellerar svenska makroekonomiska variabler – t ex i syfte att beskriva riskbilden kring dem – har påtaglig anledning att åtminstone överge antagandet om konstant störningsvarians. Ett konkret problem som annars kan uppstå är att prognososäkerhet överskattas i lugna tider och underskattas i turbulenta tider.

Employing quarterly data on GDP growth and the unemployment rate ranging from 1948Q3 to 2019Q4, we study the stability of Okun’s law in the United States. This is done by estimating hybrid time-varying Bayesian VAR models that allow for time-variation in none, one or both of the equations. Model comparison based on marginal likelihoods suggests that the relationship has not been stable. However, the amount of change in the dynamic relationship between the two variables is quantitatively very modest.

We use Bayesian techniques to estimate bivariate VAR models for Swedish unemployment rate and inflation. Employing quarterly data from 1995Q1 to 2018Q3 and new tools for model selection, we compare models with time-varying parameters and/or stochastic volatility to specifications with constant parameters and/or covariance matrix. The evidence in favour of a stable dynamic relationship between the unemployment rate and inflation is mixed. Model selection based on marginal likelihood calculations indicates that the relation is time varying, whereas the use of the deviance information criterion suggests that it is constant over time; we do, however, note consistent evidence in favour of stochastic volatility. An out-of-sample forecast exercise is also conducted, but similarly provides mixed evidence regarding which model to favour. Importantly though, even if time-varying parameters are allowed for, our results do not suggest that the Phillips curve has been flatter in more recent years. This finding thereby questions the explanation that a flatter Phillips curve is the cause of the low inflation that Sweden has experienced in recent year.

We use Bayesian techniques to estimate bivariate VAR models for Swedish unem-ployment rate and inflation. Employing quarterly data from 1995Q1 to 2018Q3 and new tools for model selection, we compare models with time-varying parameters and/or stochastic volatility to specifications with constant parameters and/or covariance matrix. The evidence in favour of a stable dynamic relationship between the unemployment rate and inflation is mixed. Model selection based on marginal like-lihood calculations indicates that the relation is time varying, whereas the use of the deviance information criterion suggests that it is constant over time; we do, however, note consistent evidence in favour of stochastic volatility. An out-of-sample forecast exercise is also conducted, but similarly provides mixed evidence regarding which model to favour. Importantly though, even if time-varying parameters are allowed for, our results do not suggest that the Phillips curve has been flatter in more recent years. This finding thereby questions the explanation that a flatter Phillips curve is the cause of the low inflation that Sweden has experienced in recent year.

Inflation did not fall as much as many economists expected as the Great Recession hit the US economy. One explanation suggested for this phenomenon is that the Phillips curve has become flatter. In this paper we investigate the stability of the US Phillips curve, employing Bayesian VARs to quarterly data from 1990Q1 to 2017Q3. We estimate bivariate models for PCE inflation and the unemployment rate under a number of different assumptions concerning the dynamics and covariance matrix. Specifically, we assess the importance of time-varying parameters and stochastic volatility. Using new tools for model selection, we find support for both time-varying parameters and stochastic volatility. Interpreting the Phillips curve as the inflation equation of our Bayesian VAR, we conclude that the US Phillips curve has been unstable. Our results also indicate that the Phillips curve may have been somewhat flatter between 2005 and 2013 than in the decade preceding that period. However, while the dynamic relations of the model appear to be subject to time variation, we note that the effect of a shock to the unemployment rate on inflation is not fundamentally different over time. Finally, a conditional forecasting exercise suggests that as far as the models are concerned, inflation may not have been unexpectedly high around the Great Recession.

It has been claimed that the fall in US inflation during the Great Recession was surprisingly small. One possible explanation for this is that the Phillips curve is unstable and that its slope was lower around the Great Recession. We investigate the importance of time-varying parameters using Bayesian vector autoregressions for inflation and unemployment. We find support for time variation in the inflation equation and an unstable Phillips curve that was somewhat flatter between 2005 and 2013. However, conditional forecasts mostly suggest that inflation was not unexpectedly high around the Great Recession, which puts the claim of a "missing disinflation" into question.

I denna artikel undersöks huruvida förhållandet mellan förändringen i arbetslöshetsgrad och BNP-tillväxt i Sverige har varit stabilt i Sverige mellan 1982och 2019. Analysen av sambandet, vilket ofta kallas Okuns lag, genomförs mednyutvecklade bayesianska metoder som möjliggör formella jämförelser mellanolika skattade modeller. Våra resultat tyder på att sambandet har varit stabiltöver tiden. De indikerar även att högre BNP-tillväxt än förväntat sänkerarbetslöshetsgraden på kort sikt

I denna artikel analyseras sambandet mellan arbetslöshet och inflation i Sverige under en period där inflationsmålspolitiken kan ses som etablerad. Resultaten indikerar att sambandet mellan arbetslöshet och inflation – vilket ofta benämns phillipskurvan – inte nödvändigtvis har varit stabilt över tiden. Vi finner dock inget stöd för att inflationen under de senaste åren skulle ha blivit mindre känslig för förändringar i arbetslösheten. Analysen pekar också på vikten av att överväga huruvida makroekonomiska samband samt de störningar som drabbar ekonomin bör modelleras som tidsvarierande, såväl för att kunna besvara akademiska frågeställningar som att ha policymodeller med relevanta empiriska egenskaper.

In this paper we assess whether the relation between the corporate bond-yield spread and the real economy has been stable over time. Using quarterly US data from 1953Q1 to 2018Q2, we estimate Bayesian VAR models which allow for drifting parameters and/or stochastic volatility and conduct formal model selection in a Bayesian setting. Our results indicate that the relation between the variables has been stable; we do, however, find strong support for stochastic volatility. We conclude that the corporate bond-yield spread’s usefulness for predicting real economic activity has not changed to a relevant extent after the Great Recession.

In this paper we assess whether the relation between the corporate bond-yield spread and the real economy has been stable over time. Using quarterly US data from 1953Q1 to 2018Q2, we estimate Bayesian VAR models which allow for drifting parameters and/or stochastic volatility and conduct formal model selection in a Bayesian setting. Our results indicate that the relation between the variables has been stable; we do, however, find strong support for stochastic volatility. We conclude that the corporate bond-yield spread’s usefulness for predicting real economic activity has not changed to a relevant extent after the Great Recession.