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This paper presents a framework for quantifying uncertainty around point forecasts for GDP, inflation and house prices in Norway. The framework combines quantile regressions using a broad set of uncertainty indicators with a skewed t-distribution, allowing for time-variation and asymmetry in the uncertainty forecasts. This approach helps provide deeper insights into the macroeconomic uncertainty surrounding forecasts than more traditional time-series models, where uncertainty is usually symmetric and with limited time-variation. Formal tests, such as the log score and the Continuous Ranked Probability Score (CRPS), show that using informative indicators tend to improve density forecasts, particularity in the medium run.

We propose a novel copula approach to producing density forecasts of economic aggregates combining models using disaggregate data. Our copula approach is more flexible compared to existing techniques, because it is applicable to any econometric model that produces density forecasts. We construct a set of Monte Carlo studies to investigate the properties of the suggested approach. In our empirical application, we use the Norwegian index for goods consumption (VKI) and the Norwegian consumer price index for underlying inflation (CPI-ATE). We find that the copula approach compares well to alternative methods using recursive out-of-sample estimation.

Forecasting and estimating core inflation has recently gained attention, especially for inflation targeting countries, following research showing that targeting headline inflation may not be optimal; a Central Bank can miss the signal due to the noise. Despite its importance there is sparse literature on estimating and forecasting core inflation in South Africa, with the focus still on measuring core inflation. This paper emphasises predicting core inflation using large time-varying parameter vector autoregressive models (TVP-VARs), factor augmented VAR, and structural break models using quarterly data from 1981Q1 to 2013Q4. We use mean squared forecast errors (MSFE) and predictive likelihoods to evaluate the forecasts. In general, we find that (i) small TVP-VARs consistently outperform all other models; (ii) models where the errors are heteroscedastic do better than models with homoscedastic errors; (iii) models assuming that the forgetting factor remains 0.99 throughout the forecast period outperforms models that allow for the forgetting factors to change with time; and (iv) allowing for structural break does not improve the predictability of core inflation. Overall, our results imply that additional information on the growth rate of the economy and interest rate is sufficient to forecast core inflation accurately, but the relationship between these three variables needs to be modelled in a time-varying (nonlinear) fashion.

There is widespread disagreement about the role of housing wealth in explaining consumption. This paper exploits liquid and illiquid wealth time series from household balance sheet data for South Africa, previously constructed by the authors, to explain fluctuations in the ratios of consumption and household debt to income in South Africa, from 1971 to 2005. The paper emphasizes the role of substantial credit liberalization and of wealth, treating credit conditions as a latent variable with key interactions with drivers of consumption and debt. Credit conditions are proxied by a spline function entering jointly estimated consumption, debt and income expectations equations in a 'latent interactive variable equation system' (LIVES). The empirical results corroborate the theory in the paper, confirming that consumption relative to income is driven by credit liberalization, fluctuations in a range of asset values and asset accumulation, uncertainty and income expectations, inter alia. The paper confirms a collateral interpretation of housing wealth on consumption as opposed to a life-cycle interpretation. The paper also throws important light on the monetary policy transmission mechanism in South Africa.

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP, consumption and investment growth, our results suggest that the news data contains information not captured by the hard economic indicators, and that the news-based data are particularly informative for forecasting consumption developments.

We ask whether a pay-as-you-go financed social security system is welfare improving in an economy with idiosyncratic productivity and aggregate business cycle risk. We show analytically that the whole welfare benefit from joint insurance against both risks is greater than the sum of benefits from insurance against the isolated risk components. One reason is the convexity of the welfare gain in total risk. The other reason is a direct risk interaction which amplifies the utility losses from consumption risk. We proceed with a quantitative evaluation of social security’s welfare effects. We find that introducing an unconditional minimum pension leads to substantial welfare gains in expectation, even net of the welfare losses from crowding out. About 60% of the welfare gains would be missing when simply summing up the isolated benefits.

In response to the COVID-19 health crisis, the French government has imposed drastic lockdown measures for a period of 55 days. This paper provides a quantitative assessment of the economic and environmental impacts of these measures in the short and long term. We use a Computable General Equilibrium model designed to assess environmental and energy policies impacts at the macroeconomic and sectoral levels. We find that the lockdown has led to a significant decrease in economic output of 5% of GDP, but a positive environmental impact with a 6.6% reduction in CO2 emissions in 2020. Both decreases are temporary: economic and environmental indicators return to their baseline trajectory after a few years. CO2 emissions even end up significantly higher after the COVID-19 crisis when we account for persistently low oil prices. We then investigate whether implementing carbon pricing can still yield positive macroeconomic dividends in the post-COVID recovery. We find that implementing ambitious carbon pricing speeds up economic recovery while significantly reducing CO2 emissions. By maintaining high fossil fuel prices, carbon taxation reduces the imports of fossil energy and stimulates energy efficiency investments while the full redistribution of tax proceeds does not hamper the recovery. Electronic supplementary material The online version of this article (10.1007/s10640-020-00488-z) contains supplementary material, which is available to authorized users.

We use a novel data set covering all domestic debit card transactions in physical terminals by Norwegian households, to nowcast quarterly Norwegian household consumption. These card payments data are free of sampling errors and are available weekly without delays, providing a valuable early indicator of household spending. To account for mixed-frequency data, we estimate various mixed-data sampling (MIDAS) regressions using predictors sampled at monthly and weekly frequency. We evaluate both point and density forecasting performance over the sample 2011Q4-2020Q1. Our results show that MIDAS regressions with debit card transactions data improve both point and density forecast accuracy over competitive standard benchmark models that use alternative high-frequency predictors. Finally, we illustrate the benefits of using the card payments data by obtaining a timely and relatively accurate nowcast of the first quarter of 2020, a quarter characterized by heightened uncertainty due to the COVID-19 pandemic.

This paper presents a computable general equilibrium model (CGEM) able to measure the impacts of the affirmative action policy set up in South Africa. In order to decrease inequalities inherited from the former regime, the government encourages firms to employ Historically Disadvantaged Persons (HDP). Through this study, we evaluate the impact of this policy on employment, poverty and inequality. To evaluate impacts on poverty and inequality, we use a CGE Top Down approach. The paper analyses two scenarios; the first one deals with the impact of affirmative action on skilled jobs. The second scenario adds to the previous by including semi skilled workers in the simulation. Both of these scenarios show a deep decrease in unemployment as well as a fall of poverty for each population groups.

(ProQuest: ... denotes formulae omitted.)1. INTRODUCTIONIn his early study, Chow (1985) reported strong evidence in favor of the Permanent Income Hypothesis (PIH) using annual observations in China from 1953 to 1982. Later, Chow (2010) re-evaluated his model for the post-economic reform regime, 1978 to 2006, then provided the same conclusion.1 Using further updated data, Chow (2011) reported weaker but similar supporting evidence for the PIH in China.We believe these findings are not convincing both theoretically and empirically. Under the PIH, optimizing consumers choose a stable path of consumption over their lifetime.2 This implies that those consumers must borrow whenever their realized current income falls below their permanent income. However, in the absence of perfect capital markets, poor consumers may not be able to access to credit markets (Shoji, Aoyagi, Kasahara, Sawada, and Ueyama, 2012), which implies that liquidity constrained consumers may fail to obey the PIH.One may claim that these consumers may still resort to informal credit markets as Guirkinger (2008) points out. We view these possibilities highly improbable in the case of China. For instance, using rural household data, Yuan and Xu (2015) show that the poor in China are severely excluded from not only formal but also informal credit markets. Therefore, it seems difficult to reconcile Chow's proposed indirect evidence of the PIH with such institutional facts about accessibility to credit markets in China.From an empirical point of view, we note that his empirical analysis focuses on the coefficient of the lagged consumption in an autoregressive (AR) model for consumption. Finding that the confidence band of that coefficient includes 1, he suggested that the PIH is consistent with Chinese annual data. However, his statistical inference may not be valid when consumption obeys an integrated process, because the conventional t-test he uses is invalid when consumption obeys an I(1) process.3 Further, his work does not implement any direct statistical tests for the predictability of consumption growth in China.This paper fills this gap by directly investigating the in-sample and the out-of-sample predictability of consumption changes in China as well as the postwar US data for comparison. Our findings suggest that consumption changes are highly predictable, which provides a clear contrast with findings shown in Chow (1985, 2010, 2011).The rest of the paper is organized as follows. Section 2 provides a data description and preliminary test results. In Section 3, we provide our major findings. Section 4 concludes.2 DATA AND PRELIMINARY ANALYSISWe obtained per capita disposable income ( ) and consumption expenditure ( ) data in China from China Statistical Yearbook (2012) following Chow (1985, 2010, 2011). Observations are annual and span from 1978 to 2012. It should be noted that observations prior to 1978 are excluded, because China began their major economic reforms since 1978, and the pre-economic reform regime data are often unreliable. We deflated all observations using the GDP deflator, obtained from the same source. All data are log transformed.The log real per capita disposable income and the log real consumption expenditures of nondurable goods and services in the US are obtained from the Federal Reserve Economic Data (FRED). Observations are quarterly and cover the period from 1952:Q1 to 2011:Q4.We first implement the augmented Dickey-Fuller (ADF) test for these variables. Results are reported in Table 1. The ADF test rejects the null of nonstationarity only for differenced series with an exception of y t in China when time trend is present. Overall, our test results imply that consumption and income are integrated series, which is also consistent with Chow's work.3. EMPIRICAL FINDINGS3.1. In-Sample AnalysisCampbell and Mankiw (1990) test the validity of the PIH in the US by empirically evaluating Hall's (1978) famous claim: Consumption follows a random walk process under the PIH. …

International audience; Kiyotaki and Wright (1989) model has exerted considerable in ‡uence in the monetary search literature. We argue that the model delivers also important insights on a broader range of macroeconomic and development issues. The analysis studies how market frictions and the liquidity of assets a¤ect the distribution of income. Experiments illustrate how the economy adjusts to shocks to assets' returns and to the matching technology. They also deal with long-run transition. An experiment interprets the reversal of fortune hypothesis as a situation in which an economy with a low-return asset takes over a similar economy with a high-return asset.

У статті наведено основні напрямки та структура розвитку промисловості України. Зроблено аналіз деяких показників галузевої структури промисловості. Обґрунтовано роль та необхідність розгляду макроекономічних показників у розрізі економічного розвитку країни. Проаналізовані деякі макроекономічні показники розвитку України. Розглянуто зв’язок галузевої структури промисловості з макроекономічними показниками та виявлено їх вплив. Основою економіки є виробництво, тобто. створення кінцевого економічного продукту. Без виробництва не може бути споживання. Виробництво матеріальних благ і послуг здійснюють такі основні галузі: промисловість, сільське господарство, будівництво, зв’язок, транспорт. Але фундаментом економіки все ж є промисловість, як провідна галузь. Розвиток промисловості впливає на темпи науково-технічного прогресу в усьому народному господарстві. Промисловість - база розширеного відтворення і економічного розвитку країни, її обороноздатності, вона забезпечує громадян країни товарами народного споживання і різного роду послугами, тому необхідно її показники вивчати більш ретельно і особливо у відповідності до галузевої структури країни. Сучасна промисловість відрізняється складністю складу галузей, виробництв і зв’язків між ними. Кожна з галузей і виробництв характеризуються різним ступенем капіталомісткості, трудомісткості, матеріаломісткості, енергоємності, водоємності, наукоємності тощо. Розвиток економічних наук та застосування математичних методів аналізу економічних процесів дозволило визначити ряд фундаментальних показників галузей промисловості, що характеризують економічний стан будь-якої держави. Такі показники отримали назву макроекономічні показники. Чітке розуміння економічної сутності цих показників і їх взаємного впливу один на одного - це основа для розробки політики регулювання економічних процесів в державі, тому дослідження їх складових у залежності від структурної складової промисловості є нагальною задачею науковців у сучасній економічній системі. Це необхідно для впливу на їх поліпшення, що в цілому буде сприяти закріпленню позитивного іміджу країни на світовій арені. The article gives the main directions and structure of the development of industry in Ukraine. An analysis of some indicators of the sectoral structure of the industry is made. The role and necessity of considering macroeconomic indicators in the context of economic development of the country are substantiated. Some macroeconomic indicators of Ukraine's development are analyzed. The connection of the branch structure of the industry with macroeconomic indicators is considered and their influence is revealed. The basis of the economy is production, ie. creation of the final economic product. Without production, there can be no consumption. The production of material goods and services is carried out by the following main branch: industry, agriculture, construction, communications, transport. But the foundation of the economy is still an industry, as a leading branch. The development of industry affects the pace of scientific and technological progress throughout the national economy. The industry is the base of expanded reproduction and economic development of the country, its defense capacity, it provides citizens of the country with consumer goods and various services, therefore it is necessary to study its indicators more carefully and especially in accordance with the sectoral structure of the country. Modern industry is characterized by the complexity of the branches, industries, and connections between them. Each of the branches and industries is characterized by varying degrees of capital intensity, labor intensity, material intensity, energy intensity, environmental capacity, knowledge intensity, etc. The development of economic sciences and the application of mathematical methods for analyzing economic processes allowed to determine the number of fundamental indicators of industries that characterize the economic situation of any state. Such indicators are called macroeconomic indicators. A clear understanding of the economic nature of these indicators and their mutual influence on each other is the basis for developing a policy of regulating economic processes in the state; therefore, the study of their components, depending on the structural component of the industry, is an urgent task of scientists in the modern economic system. It is necessary to influence their improvement, which in general will help to consolidate the positive image of the country on the world stage.

Nous comparons les prévisions de croissance de l'économie française à l'horizon 2020 réalisées entre septembre et début novembre 2018 par 18 organismes (publics et privés, dont l'OFCE). Après avoir augmenté de 2,3 % en 2017, l'activité ralentirait pour l'ensemble des prévision- nistes interrogés à 1,6 % en moyenne en 2018. Il n'y a pas d'accélération prévue à l'horizon de l'exercice de prévision : l'activité progresserait en moyenne de 1,6 % en 2019 et de 1,5 % 2020 (avec 8 instituts sur 12 qui prévoient un ralentissement). Mais les moteurs de la croissance changeraient. En 2017, la croissance avait été tirée par une forte contribution de la demande intérieure hors stocks tandis que le commerce extérieur jouait négativement. L'histoire est toute autre en 2018, le commerce extérieur, par sa contribution positive, contribuerait à compenser partiellement une demande intérieure moins dynamique. En 2019 et 2020, c'est l'inverse. L'accélération de la consommation des ménages permise par l'amélioration des revenus soutiendrait la croissance, tandis que l'investissement resterait solide. L'environnement international serait moindre favorable et les risques sur la croissance, plutôt orientés à la baisse. Si un consensus existe autour de ce scénario central, il masque malgré tout des divergences entre instituts liées notamment aux hypothèses relatives au positionnement de l'économie française dans son cycle, et donc au degré de tensions dans l'économie. Pour tous, l'inflation reste globalement modérée en prévision (entre 1,4 % et 1,9 % en 2020 selon les instituts) mais l'inflation sous-jacente s'accélère, tout en restant inférieure à 2 %, et certains instituts considèrent que des contraintes d'offre existent, notamment sur le marché du travail. Le taux de chômage baisserait de 9,4 % en 2017 à entre 8,1 % pour les plus optimistes à 9,1 % les plus pessimistes en fin de période. La progression des salaires resterait malgré tout contenue sur la période (avec un maximum à 2,6 % en 2020). L'impact positif des réformes passées et en cours sur la croissance du PIB et la compétitivité des entreprises ne ressort pas véritablement des scénarios. La France est sortie de la Procédure de déficit excessif en 2018 et tous les instituts prévoient le respect des règles budgétaires concernant le déficit public, qui resterait en-deçà du seuil des 3 % à l'horizon 2020. Néanmoins, le déficit se dégraderait 2019, du fait de mesures exceptionnelles (remboursement aux entreprises de la taxe sur les dividendes et transformation du CICE en baisses de charges sociales employeurs) et d'une amélioration de la composante conjoncturelle plus limitée qu'en 2017. En 2020, il serait compris entre 2,7 % et 1,6 % du PIB.

Nous comparons les prévisions de croissance de l'économie française à l'horizon 2020 réalisées entre septembre et début novembre 2018 par 18 organismes (publics et privés, dont l'OFCE). Après avoir augmenté de 2,3 % en 2017, l'activité ralentirait pour l'ensemble des prévision- nistes interrogés à 1,6 % en moyenne en 2018. Il n'y a pas d'accélération prévue à l'horizon de l'exercice de prévision : l'activité progresserait en moyenne de 1,6 % en 2019 et de 1,5 % 2020 (avec 8 instituts sur 12 qui prévoient un ralentissement). Mais les moteurs de la croissance changeraient. En 2017, la croissance avait été tirée par une forte contribution de la demande intérieure hors stocks tandis que le commerce extérieur jouait négativement. L'histoire est toute autre en 2018, le commerce extérieur, par sa contribution positive, contribuerait à compenser partiellement une demande intérieure moins dynamique. En 2019 et 2020, c'est l'inverse. L'accélération de la consommation des ménages permise par l'amélioration des revenus soutiendrait la croissance, tandis que l'investissement resterait solide. L'environnement international serait moindre favorable et les risques sur la croissance, plutôt orientés à la baisse. Si un consensus existe autour de ce scénario central, il masque malgré tout des divergences entre instituts liées notamment aux hypothèses relatives au positionnement de l'économie française dans son cycle, et donc au degré de tensions dans l'économie. Pour tous, l'inflation reste globalement modérée en prévision (entre 1,4 % et 1,9 % en 2020 selon les instituts) mais l'inflation sous-jacente s'accélère, tout en restant inférieure à 2 %, et certains instituts considèrent que des contraintes d'offre existent, notamment sur le marché du travail. Le taux de chômage baisserait de 9,4 % en 2017 à entre 8,1 % pour les plus optimistes à 9,1 % les plus pessimistes en fin de période. La progression des salaires resterait malgré tout contenue sur la période (avec un maximum à 2,6 % en 2020). L'impact positif des réformes passées et en cours sur la croissance du PIB et la compétitivité des entreprises ne ressort pas véritablement des scénarios. La France est sortie de la Procédure de déficit excessif en 2018 et tous les instituts prévoient le respect des règles budgétaires concernant le déficit public, qui resterait en-deçà du seuil des 3 % à l'horizon 2020. Néanmoins, le déficit se dégraderait 2019, du fait de mesures exceptionnelles (remboursement aux entreprises de la taxe sur les dividendes et transformation du CICE en baisses de charges sociales employeurs) et d'une amélioration de la composante conjoncturelle plus limitée qu'en 2017. En 2020, il serait compris entre 2,7 % et 1,6 % du PIB.

This study evaluates the economic impact of a shift towards renewable electricity mix in the Netherlands using the neo-Keynesian CGEM ThreeME (Multi-sector Macroeconomic Model for the Evaluation of Environmental and Energy policy). This scenario has been inspired by the Urgenda's report ‘Energy 100% Sustainable in the Netherlands by 2030’, which have been quantified using the Energy Transition Model (ETM) developed by Quintel. Using the output of the ETM regarding the change in the electricity generation shares as input in ThreeME, we derive the impact in terms of key economic variables (GDP, employment, investment, value-added, prices, trade, tax revenue, etc.). We find that transition to renewable energy may have a positive impact on the Dutch economy, creating almost 50 000 new jobs by 2030 and adding almost 1% of gross domestic product. © 2017

Alors que l'INSEE vient de publier une première estimation de la croissance française de 2017 (1,9 %), nous comparons les prévisions pour 2018 et 2019 réalisées par 18 organismes (publics et privés, dont l'OFCE) entre septembre et décembre 2017. Pour tous la reprise semble solidement enclenchée et durable, avec une croissance moyenne prévue de 1,8 % en 2018 puis de 1,7 % en 2019 : les prévisions sont assez proches pour 2018 (1,7 % à 2 %) mais s'étalent de 1,4 % à 2,2 % en 2019 (avec 8 instituts sur 15 qui prévoient un ralentissement). La consommation privée accélérerait un peu (1,6 % en 2018 et 1,7 % en 2019), avec des écarts nets entre instituts. En effet, l'emploi progresserait entre 0,6 et 1,9 % en 2019 et les salaires entre 1,3 % et 2,6 %. Le diagnostic sur les salaires dépend du degré de tensions sur le marché du travail, de l'impact de l'inflation et des gains de productivité et de l'effet de la réforme du marché du travail de 2017 (décentralisation des négociations collectives). L'inflation resterait modérée (1,4 % en 2019). Le taux de chômage baisserait à 8,8 % en moyenne en 2019 mais les prévisions varient entre 8,1 % et 9,2 %. Pour tous les instituts, le déficit public respecterait dès 2017 le seuil de 3 % du PIB. La France pourrait alors sortir de la Procédure de Déficit Excessif en 2018. Le déficit resterait cependant élevé, du fait de mesures exceptionnelles (remboursement aux entreprises de la taxe sur les dividendes récemment invalidée par le Conseil constitutionnel et transformation du CICE en baisses de charges sociales employeurs en 2019).

This paper employs classical bivariate, slab-and-spike variable selection, Bayesian semi-parametric shrinkage, and factor-augmented predictive regression models to forecast US real private residential fixed investment over an out-of-sample period from 1983Q1 to 2005Q4, based on in-sample estimates for 1963Q1–1982Q4. Both large-scale (188 macroeconomic series) and small-scale (20 macroeconomic series) slab-and-spike variable selection, and Bayesian semi-parametric shrinkage, and factor-augmented predictive regressions, as well as 20 bivariate regression models, capture the influence of fundamentals in forecasting residential investment. We evaluate the ex post out-of-sample forecast performance of the 26 models using the relative average mean square error for one-, two-, four-, and eight-quarter-ahead forecasts and test their significance based on the McCracken (2004, J Econom 140:719–752, 2007) mean-square-error F statistic. We find that, on average, the slab-and-spike variable selection and Bayesian semi-parametric shrinkage models with 188 variables provides the best forecasts among all the models. Finally, we use these two models to predict the relevant turning points of the residential investment, via an ex ante forecast exercise from 2006Q1 to 2012Q4. The 188 variable slab-and-spike variable selection and Bayesian semi-parametric shrinkage models perform quite similarly in their accuracy of forecasting the turning points. Our results suggest that economy-wide factors, in addition to specific housing market variables, prove important when forecasting in the real estate market.

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related to the target variable nonlinearly. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predictive regression model is based on a shrinkage estimator in order to avoid overfitting. We extend the kernel ridge regression methodology to enable its use for economic time series forecasting, by including lags of the dependent variable or other individual variables as predictors, as is typically desired in macroeconomic and financial applications. Both Monte Carlo simulations and an empirical application to various key measures of real economic activity confirm that kernel ridge regression can produce more accurate forecasts than traditional linear and nonlinear methods for dealing with many predictors based on principal components.

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 the studied models which rely 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.

Summary We study the role of consumer confidence in forecasting real personal consumption expenditure, and contribute to the extant literature in three substantive ways. First, we re-examine existing empirical models of consumption and consumer confidence, not only at the quarterly frequency, but using monthly data as well. Second, we employ real-time data in addition to commonly used revised vintages. Third, we investigate the role of consumer confidence in a rich information context. We produce forecasts of consumption expenditures with and without consumer confidence measures using a dynamic factor model and a large, real-time, jagged-edge dataset. In a robust way, we establish the important role of confidence surveys in improving the accuracy of consumption forecasts, manifesting primarily through the services component. During the recession of 2007–2009, sentiment is found to have a more pervasive effect on all components of aggregate consumption: durables, non-durables and services. Copyright © 2015 John Wiley & Sons, Ltd.

We analyze forecasts of consumption, nonresidential investment, residential investment, government spending, exports, imports, inventories, gross domestic product, inflation, and unemployment prepared by the staff of the Board of Governors of the Federal Reserve System for meetings of the Federal Open Market Committee from 1997 to 2008, called the Greenbooks. We compare the root mean squared error, mean absolute error, and the proportion of directional errors of Greenbook forecasts of these macroeconomic indicators to the errors from three forecasting benchmarks: a random walk, a first-order autoregressive model, and a Bayesian model averaged forecast from a suite of univariate time-series models commonly taught to first-year economics graduate students. We estimate our forecasting benchmarks both on end-of-sample vintage and real-time vintage data. We find that Greenbook forecasts significantly outperform our benchmark forecasts for horizons less than one quarter ahead. However, by the one-year forecast horizon, typically at least one of our forecasting benchmarks performs as well as Greenbook forecasts. Greenbook forecasts of the personal consumption expenditures and unemployment tend to do relatively well, while Greenbook forecasts of inventory investment, government expenditures, and inflation tend to do poorly.

In this study a comparative analysis of the forecasts accuracy for Spain (developed country) and Romania (developing country) was developed for the crisis period (2009 - 2013). The providers are national forecasters: Bank of Spain and FUNCAS (Spanish Savings Banks Foundation) for Spain and two anonymous experts for Romania (E1 and E2). Only for the unemployment rate the Spanish institutes provided more accurate forecasts, for the rest of the variables (inflation rate, private consumption and GDP growth) the Romanian institutes giving more accurate predictions. However, the results are contradictory for the accuracy assessment in each country, the U1 Theil's statistic and the accuracy tests (Diebold-Mariano test and Wilcoxon's signed rank test) indicating different hierarchies. All in all, for inflation rate, unemployment rate and GDP growth in Romania, E2 provided more accurate forecasts. In Spain, FUNCAS offered better forecasts for GDP growth and private consumption during 2009 - 2013.

The Great Recession of 2007:IV-2009:II sparked great interest in understanding uncertainty and its effects on the macroeconomy. This paper introduces a new approach to measure uncertainty. We start from the same premise as in Jurado et al. (2014), that is: "What matters for economic decision making is whether the economy has become more or less predictable; that is, less or more uncertain." However, as opposed to Jurado et al. (2014), the uncertainty index we propose relies on the unconditional likelihood of the observed outcome. More specifically, our proposed index is the percentile in the historical distribution of forecast errors associated with the realized forecast error.

Standard economic models assume that the demand for expert predictions arises only under the conditions in which individuals are uncertain about the underlying process generating the data and there is a strong belief that past performances predict future performances. We set up the strongest possible test of these assumptions. In contrast to the theoretical suggestions made in the literature, people are willing to pay for predictions of truly random outcomes after witnessing only a short streak of accurate predictions live in the lab. We discuss potential explanations and implications of such irrational learning in the contexts of economics and finance. © 2015 The President and Fellows of Harvard College and the Massachusetts Institute of Technology

We apply meta regression analysis to a unique data set of 104 studies on multiplier effects with 1069 reported multipliers in order to derive stylized facts and to quantify the differing effectiveness of the composition of fiscal impulses, adjusted for the interference of study-design characteristics and sample specifics. As a major result, we find that public spending multipliers are close to one and about 0.3 to 0.4 units larger than tax and transfer multipliers. Public investment multipliers are even larger by approximately 0.5 units. Reported multipliers vary with study-design, thus, policy consulting based on a certain multiplier study should lay open by how much specification affects the results. Our meta analysis provides guidance concerning influential factors, their sign and magnitude.

This paper exploits a data rich environment to provide direct econometric estimates of time-varying macroeconomic uncertainty, defined as the common volatility in the unforecastable component of a large number of economic indicators. Our estimates display significant independent variations from popular uncertainty proxies, suggesting that much of the variation in the proxies is not driven by uncertainty. Quantitatively important uncertainty episodes appear far more infrequently than indicated by popular uncertainty proxies, but when they do occur, they are larger, more persistent, and are more correlated with real activity. Our estimates provide a benchmark to evaluate theories for which uncertainty shocks play a role in business cycles.

We study forecasts of real GDP growth using a large panel of individual forecasts from 36 advanced and emerging economies over the period 1989–2010. We show that the degree of information rigidity in average forecasts is substantially higher than that in individual forecasts. Individual-level forecasts are updated quite frequently, a behavior which is more in line “noisy” information models (Woodford, 2002; Sims, 2003) than with the assumptions of the sticky information model (Mankiw & Reis, 2002). While there are cross-country variations in information rigidity, there are no systematic differences between advanced and emerging economies.

Die amtliche Statistik hat die Angaben zum Bruttoinlandsprodukt der ostdeutschen Flächenländer für die Jahre seit 2000 um jährlich rund 3% erhöht. In dieser Korrektur kommen auch konzeptionelle Erweiterungen des gesamtwirtschaftlichen Rechnungswesens zum Tragen. Insbesondere betrifft das Forschungs- und Entwicklungsleistungen, die jetzt wie eine Investition in ein Vermögensgut behandelt werden. Es zeigt sich, dass der Osten in diesem Zukunftsbereich gegenüber dem Westen stärker zurückliegt, als bisher beziffert worden ist.

This study is intended to demonstrate that the downturn in fixed capital formation and investment surpassed the decline in GDP; among the OECD countries Hungary witnessed the 9th largest shortfall of the investment rate compared to pre-crisis levels. The growth rate of Hungarian working capital outflows surpassed that of FDI inflows. The service fee payment of PPP investment contributed to the budget deficit by around 0.5 per cent of GDP per annum. The structure of whole-economy fixed investment underwent a considerable transformation: manufacturing saw a spectacular expansion, while the share of public administration and water supply grew to a lesser degree. The contribution of real estate, electricity and gas supply, education and transportation decreased markedly. The structural changes in public sector investment are reflected in the output of fixed capital formation, which increased by 2.1 in the central budget and by 12.3 per cent at local governments. The total amount of investment grants doubled in the period between 2009 and 2013. In the sector of non-financial corporations, the ratio of grants to GDP rose to 1.3 per cent in 2011, 1.4 per cent in 2012, and 1.9 per cent in 2013 compared to 1.2 and 1.1 per cent in 2009 and 2010, respectively. Besides net EU transfers, the expansion of grants was also an important contributor to the upswing in investment activity in 2013–2014.

Az európai növekedési potenciál fokozatos, ám több évtizeden át látens eróziója az elmúlt másfél évtizedben - versenyképességi és alkalmazkodási problémáinak kiéleződésével párhuzamosan - egyre nyíltabb formában jelent meg. Az EU-15 országai termelékenységének felzárkózása az Egyesült Államokéhoz - fokozatos mérséklődés után - az 1990-es évek közepén megtört, majd növekedési dinamikája egyre inkább elmaradt fő versenytársáétól. A teljes tényezőtermelékenységbeli különbségek csekély számú iparágban összpontosulnak: az elektronikai berendezések előállítása, a nagy- és a kiskereskedelem, az ingatlan- és egyéb üzleti szolgáltatások, illetve a pénzügyi szolgáltatások területén. A fő okok a termék- és munkaerőpiacok működésének eltéréseiben, az Egyesült Államokat jellemző intenzívebb versenykörülményekben, illetve egyes európai részpiacok túlszabályozásában keresendők. Lényeges szerepet játszanak továbbá az innovatív szektorok adminisztratív és pénzügyi belépési korlátai. Journal of Economic Literature (JEL) kód: E27, F15, F43, O40, O47., Gradual, latent erosion of European growth potential over several decades - parallel exacerbation of problems of competitiveness and adaptation - has been appearing in an increasingly open form. The improvement in the productivity of the EU 15 countries compared with the United States eased steadily and then ceased in the mid-1990s, after which its growth dynamic fell behind that of its main competitor. The whole factor-productivity differences were centred on a small number of industries: production of electronic equipment, wholesale and retail trading, real-estate and other commercial services, and financial services. The main causes can be sought in differences in the operation of product and labour markets, the more intensive competition conditions characteristic of the United States, and the excessive regulation of certain partial European markets. An essential role is also played by the administrative and financial entry restrictions on innovative sectors.

This paper develops a dynamic structural life-cycle model to study how heterogeneous health and medical spending shocks a¤ect the savings behavior of the elderly. Individuals are allowed to respond to health shocks in two ways: they can directly pay for their health care expenses (self-insure) or they can rely on health insurance contracts. There are two possible insurance options, one through formal contracts and another through informal care provided by family. Formal contracts may be a¤ected by asymmetric information problems, whereas informal insurance depends on social ties (cohesion) and on bequeathable wealth. I estimate the model on SHARE data using simulated method of moments for four levels of wealth in a sample of single retired Europeans. Counterfactual experiments show that health, medical spending and health insurance are indeed the main drivers of the slow wealth decumulation in old age. I also fi?nd that social cohesion rises with age, declines with wealth and is higher in Mediterranean countries than in Central European and Scandinavian countries. Finally, high social cohesion appears typically associated with increased life expectancy.

When forecasting, all available information should be used. As the most recent indicators are mostly published in monthly or higher frequency while the GDP is released in quarterly frequency, this can pose a problem in an econometric framework. This paper presents the KOF short-term indicator for international forecasts, which uses both bridge equations as well as a MIDAS approach. The forecast performance of the models is then assessed by conducting a real-time experiment using a reduced dataset for the US. Even with this reduced set forecast performance can be increased by up to 25 percent in comparison to an autoregressive model.

The Vision of the Eco-Bio-Economy is to sustain development of the humankind welfare in all forms, through an economy of future dedicated to human life through the rational use of the environmental resources. The present work attempts to discuss the issues that humanity faces at the beginning of a new global economic paradigm. The minimum point of the financial crisis started in 2008 meets the final years of the decline phase of the long term global economic cycle. The feeling is one of lack of vision on the part of Governments, of improvisation, of passive reaction, such as seeing and doing. One feels that the economic context is worn out , dysfunctional because of deep recovery problems. The perception, not far from the taugh reality, is that of a national competition meant to minimize losses caused by the financial crisis and to use beggar thy neighbor types of policies, similar to finding the way out of the crisis on the expense of others.

In the recent literature on nowcasting, the use of the so-called bridge models is advocated. These are simple regression models that use data on mixed frequencies, usually with the lower frequency data serving as dependent variables and the higher frequency data as explanatory variables. In this note we investigate whether the use of such models can lead to performance enhancements in forecasting real GDP growth for Greece. This is an interesting and instructive exercise because of the obvious break in Greek real GDP growth during the crisis but also, and more importantly, because of the potential usefulness of such models in forecasting the anticipated recovery in Greek growth. Since many monthly activity indicators are released in advance of GDP growth it is interesting to see how the structure and timing of bridge models can lead to potential improvements in forecasting growth. Our results indicate that by using three of the most important monthly activity indicators such performance enhancements are indeed possible.

The paper characterizes the optimal tax scheme in an open economy with structural inefficiencies on the labor market and on government size. On analytical grounds first, we show that the economy can use fiscal revaluation to exploit the terms of trade externality and to dampen the impact of an excessive public spending. However, if real labor market rigidities are large enough, fiscal devaluation may be desirable. Second, we provide a quantitative assessment of the optimal tax reform using France as the benchmark economy. Our results show that France would benefit more from fiscal devaluation than a economy where the labor market is more flexible, as the US. We also show that the welfare gains from the optimal tax reform crucially depend on the ability of the government to target its optimal size., Cet article détermine le régime fiscal optimal dans une économie ouverte caractérisée par des inefficiences structurelles liées au marché du travail et à la taille de l’Etat. De façon analytique, nous montrons d’abord que la réévaluation fiscale permet d’exploiter l’externalité des termes de l’échange et d’atténuer l’impact d’une dépense publique excessive.Toutefois, si les rigidités sur le marché du travail sont suffisamment grandes, la dévaluation fiscale peut être préférable. Deuxièmement, nous fournissons une évaluation quantitative d’une réforme adoptant cette fiscalité optimale en utilisant la France comme économie de référence. Nos résultats montrent que la France bénéficierait plus d’une dévaluation fiscale qu’une économie où le marché du travail est plus flexible, comme lesÉtats-Unis. Nous montrons également que les gains de bien-être de la réforme fiscale dépendent essentiellement de la capacité du gouvernement à revenir à sa taille optimale.

Recent work has analyzed the forecasting performance of standard dynamic stochastic general equilibrium (DSGE) models, but little attention has been given to DSGE models that incorporate nonlinearities in exogenous driving processes. Against that background, we explore whether incorporating stochastic volatility improves DSGE forecasts (point, interval, and density). We examine real-time forecast accuracy for key macroeconomic variables including output growth, inflation, and the policy rate. We find that incorporating stochastic volatility in DSGE models of macroeconomic fundamentals markedly improves their density forecasts, just as incorporating stochastic volatility in models of financial asset returns improves their density forecasts.

The global financial crisis and the ensuing criticism of macroeconomics have inspired researchers to explore new modeling approaches. There are many new models that deliver improved estimates of the transmission of macroeconomic policies and aim to better integrate the financial sector in business cycle analysis. Policy making institutions need to compare available models of policy transmission and evaluate the impact and interaction of policy instruments in order to design effective policy strategies. This paper reviews the literature on model comparison and presents a new approach for comparative analysis. Its computational implementation enables individual researchers to conduct systematic model comparisons and policy evaluations easily and at low cost. This approach also contributes to improving reproducibility of computational research in macroeconomic modeling. Several applications serve to illustrate the usefulness of model comparison and the new tools in the area of monetary and fiscal policy. They include an analysis of the impact of parameter shifts on the effects of fiscal policy, a comparison of monetary policy transmission across model generations and a cross-country comparison of the impact of changes in central bank rates in the United States and the euro area. Furthermore, the paper includes a large-scale comparison of the dynamics and policy implications of different macro-financial models. The models considered account for financial accelerator effects in investment financing, credit and house price booms and a role for bank capital. A final exercise illustrates how these models can be used to assess the benefits of leaning against credit growth in monetary policy.

The literature documents a heterogeneous asset price response to macroeconomic news announcements: Some announcements have a strong impact on asset prices and others do not. In order to explain these differences, we estimate a novel measure of the intrinsic value of a macroeconomic announcement, which we define as the announcement's ability to nowcast GDP growth, inflation, and the Federal Funds Target Rate. Using the same nowcasting framework, we then decompose this intrinsic value into the announcement's characteristics: its relation to fundamentals, timing, and revision noise. We find that in the 1998{2013 period, a significant fraction of the variation in the announcements' price impact on the Treasury bond futures market can be explained by differences in intrinsic value. Furthermore, our novel measure of timing explains significantly more of this variation than the announcements' relation to fundamentals, reporting lag (which previous studies have used as a measure of timing), or revision noise

Previous studies have shown that the effectiveness of monetary policy depends, to a large extent, on the market expectations of its future actions. This paper proposes an econometric framework to address the effect of the current state of the economy on monetary policy expectations. Specifically, we study the effect of contractionary (or expansionary) demand (or supply) shocks hitting the euro area countries on the expectations of the ECB.s monetary policy in two stages. In the first stage, we construct indexes of real activity and inflation dynamics for each country, based on soft and hard indicators. In the second stage, we use those indexes to provide assessments on the type of aggregate shock hitting each country and assess its effect on monetary policy expectations at different horizons. Our results indicate that expectations are responsive to aggregate contractionary shocks, but not to expansionary shocks. Particularly, contractionary demand shocks have a negative effect on short term monetary policy expectations, while contractionary supply shocks have negative effect on medium and long term expectations. Moreover, shocks to different economies do not have significantly different effects on expectations, although some differences across countries arise.

This document provides an overview of the theoretical foundations and general assumptions of the WVU Econometric Input-Output (ECIO) model. WVU Econometric Input-Output (ECIO) model (hereafter, ECIO model) is a time-series enabled hybrid econometric input-output (IO) model that combines the capabilities of econometric modeling with the strengths of IO modeling. It is designed to facilitate the estimation of economic (specifically, employment and income) impacts of energy technology development, deployment, and operation over a specified forecast period.

Using the extended version of the Blanchard and Perotti SVAR technique, this paper attempts to empirically predict the growth enhancing effect of discretionary fiscal policy shocks in both short- and long-run in Turkey over the period 2006:Q1-2015:Q1. Unlike previous studies which have mainly focused on fiscal policy instruments taxes and government spending at the aggregate level, this paper considers these instruments at the component level, and then attempts to analyze comparatively the effect of changes in each component on growth. The findings of the paper show that growth enhancing effect of discretionary fiscal policy shocks varies according to its components. However, discretionary fiscal policy shocks at the component level indicate mixed results. In the short-run, only the shocks to government spending have a Keynesian effect. In all other cases, discretionary fiscal policy shocks seem to capture a weak Keynesian and/or non-Keynesian effect in the case of Turkey.

When markets are incomplete, social security can partially insure against idiosyncratic and aggregate risks. We incorporate both risks into an analytically tractable model with two overlapping generations. We derive the equilibrium dynamics in closed form and show that the joint presence of both risks leads to overproportional risk exposure for households. This implies that the whole benefit from insurance through social security is greater than the sum of the benefits from insurance against each of the two risks in isolation. We measure this through interaction effects which appear even though the two risks are orthogonal by construction. While the interactions unambiguously increase the welfare benefits from insurance, they can increase or decrease the welfare costs from crowding-out of capital formation. The net effect depends on the relative strengths of the opposing forces., International Tax and Public Finance, 22 (4), ISSN:1573-6970, ISSN:0927-5940

One major concern regarding the recent financial crisis that hit the U.S. and several other OECD countries is that it may have worsened the pattern of unemployment persistence in those countries where the rate of unemployment has remained above pre–crisis levels. In this context, we use mean bias-corrected parameter estimator and bootstrap permutation test methods with a moving window to test for changes in the pattern of unemployment persistence in 29 OECD countries before and after the recent financial crisis using monthly aggregated and quarterly disaggregated data. We estimate the most likely date of change in the trend of unemployment and use this information to compute an unbiased scalar measure of persistence to test whether the recent financial crisis has produced any significant change in the pattern of unemployment persistence. We find evidence of an increased unemployment persistence in several countries which is correlated with the recent financial crisis.

This report presents long-term fiscal and economic projections for Canada, the provinces and the territories for the 2014-2038 period, and discusses their implications for budgetary balance at the provincial/territorial level. In particular, it examines whether economic growth and hence revenue growth (assuming no major changes in tax policy) will be sufficient to fund likely spending pressures. Economic growth is generally projected to be slower over the next 24 years than since 2000. As a result, all, or almost all, provinces and territories, depending upon the economic assumptions, will not be able to meet the test of balancing revenue growth with growth in public spending. Hence, without tax rate increases or action to curtail spending growth, there will be pressure for progressively larger deficits.

This paper examines the causes of the exceptionally marked fall in non-construction investment in Italy since 2007. Non-financial private services were the main driver of the decline in the aggregate investment rate, but all sectors weighed in negatively; the reallocation of value added away from industry was a further drag on investment. In concordance with survey findings, an aggregate model of investment indicates that even during the recent double recession the most important driver of capital accumulation was demand conditions. The user cost of capital had a substantial negative impact in the acute phases of the sovereign debt crisis, but since 2013 its contribution has been positive, thanks to the ECB’s expansionary monetary policy. The constraints on capital accumulation imposed by tight credit supply conditions were particularly severe in 2009 and 2012. Finally, uncertainty provided a sizeable drag on investment growth not only during the global financial crisis but also in the last two years. The significance of these determinants of investment is confirmed also by a disaggregated model for the thirteen manufacturing branches.

The linear-quadratic (LQ) optimization is a close to standard technique in the optimal control framework. LQ is very well researched and there are many extensions for more sophisticated scenarios like nonlinear models. Usually, the quadratic objective function is taken as a prerequisite for calculating derivative-based solutions of optimal control problems. However, it is not clear whether this framework is so universal as it is considered. In particular, we address the question on whether the objective function specification and the corresponding penalties applied, are well suited in case of a large exogenous shock an economy can experience because of, e.g., the European debt crisis. While one can still efficiently minimize quadratic deviations in state and control variables around policy targets, the economy itself has to go through a period of turbulence with economic indicators, such as unemployment, inflation or public debt, changing considerably over time. In this study we test four alternative designs of the objective function: a least median of squares based approach, absolute deviations, cubic and quartic objective functions. The analysis is performed based on a small-scale model of the Austrian economy and finds that there is a certain trade-off between quickly finding optimal solution using the LQ technique (reaching defined policy targets) and accounting for alternative objectives, such as limiting volatility in the economic performance.

This paper introduces a Divisia monetary aggregate for Germany and explores its information content for the Great Recession. Divisia money and the corresponding simple sum aggregate are highly correlated in normal times but begin to diverge before the crisis. Out of sample forecast analysis and a conditional forecast exercise show that the predictive content of this divergence for the Great Recession is not only statistically significant, but also economically important.

"It is broadly accepted that two aspects regarding the modeling strategy are essential for the accuracy of forecast: a parsimonious model focusing on the important structures, and the quality of prospective information. Here, we establish a Global VAR framework, a technique that considers a variety of spatio-temporal dynamics in a multivariate setting, that allows for spatially heterogeneous slope coefficients, and that is nevertheless feasible for data without extremely long time dimension. Second, we use this framework to analyse the prospective information regarding the economy due to spatial co-development of regional labour markets in Germany. The predictive content of the spatially interdependent variables is compared with the information content of various leading indicators which describe the general economic situation, the tightness of labour markets and environmental impacts like weather. The forecasting accuracy of these indicators is investigated for German regional labour-market data in simulated forecasts at different horizons and for several periods. Germany turns out to have no economically dominant region (which reflects the polycentric structure of the country). The regions do not follow a joint stable long run trend which could be used to implement cointegration. Accounting for spatial dependence improves the forecast accuracy compared to a model without spatial linkages while using the same leading indicator. Amongst the tested leading indicators, only few produce more accurate forecasts when included in a GVAR model, than the GVAR without indicator. IAB-" (Author's abstract, IAB-Doku) ((en))

We build a dynamic stochastic general equilibrium model with five sectors (1 - mining; 2 - manufacturing; 3 - electricity, gas and water; 4 - trade, transport and communication; 5 - other). The model is estimated on 29 time-series of Russia statistical data. We analyse the out-of-sample forecasting prowess of the model and derive implications for economic policy.

The assumption of rational expectations is potentially a serious source of misspecification in DSGE models. Many recent theories of expectations formation have relaxed rational expectations and improved the predictive properties of benchmark macroeconomic models. Problematically, the space of possible theoretical deviations from rational expectations is very large, especially since the aggregate consequences of deviations from rational expectations in equilibrium may not be directly measurable using existing surveys of expectations. This paper provides evidence on which small reduced-form state-contingent deviations from rational expectations yield the most improvement in replicating features of macroeconomic time series, and which aspects of model misspecification are and are not ameliorated by these small deviations from rational expectations. The findings: a) The data favor deviations from rational expectations among firms in which they over-estimate the persistence of inflation. b) Relaxing rational expectations in a New Keynesian model partially substitutes for the additional structural mechanisms in the larger Smets Wouters (2007) model. Relaxing rational expectations within the Smets Wouters (2007) model improves that model’s ability to reproduce some of the spectral coherencies between output growth, investment growth, and labor supply. The mechanism is a combination of shocks to beliefs themselves and the role that deviations from rational expectations have in changing the propagation of other shocks.