Graph and download economic data for JLN 1-Year Ahead Macroeconomic Uncertainty (JLNUM12M) from Jul 1960 to Dec 2024 about 1-year, uncertainty, and USA.

Graph and download economic data for JLN 3-Month Ahead Macroeconomic Uncertainty (JLNUM3M) from Jul 1960 to Apr 2025 about uncertainty, 3-month, and USA.

Supplementary information files for the article Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises

Abstract: This paper studies the US and global economic fundamentals that exacerbate emerging stock markets volatility and can be considered as systemic risk factors increasing financial stability vulnerabilities. We apply the bivariate HEAVY system of daily and intra-daily volatility equations enriched with powers, leverage, and macro-effects that improve its forecasting accuracy significantly. Our macro-augmented asymmetric power HEAVY model estimates the inflammatory effect of US uncertainty and infectious disease news impact on equities alongside global credit and commodity factors on emerging stock index realized volatility. Our study further demonstrates the power of the economic uncertainty channel, showing that higher US policy uncertainty levels increase the leverage effects and the impact from the common macro-financial proxies on emerging markets’ financial volatility. Lastly, we provide evidence on the crucial role of both financial and health crisis events (the 2008 global financial turmoil and the recent Covid-19 pandemic) in raising markets’ turbulence and amplifying the volatility macro-drivers impact, as well.

This paper uses a large vector autoregression to measure international macroeconomic uncertainty and its effects on major economies. We provide evidence of significant commonality in macroeconomic volatility, with one common factor driving strong comovement across economies and variables. We measure uncertainty and its effects with a large model in which the error volatilities feature a factor structure containing time-varying global components and idiosyncratic components. Global uncertainty contemporaneously affects both the levels and volatilities of the included variables. Our new estimates of international macroeconomic uncertainty indicate that surprise increases in uncertainty reduce output and stock prices, adversely affect labor market conditions, and in some economies lead to an easing of monetary policy.

Uncertainty is an amorphous concept. It reflects uncertainty in the minds of consumers, managers, and policymakers about possible futures. It is also a broad concept, including uncertainty over the path of macro phenomena like GDP growth, micro phenomena like the growth rate of firms, and noneconomic events like war and climate change. In this essay, I address four questions about uncertainty. First, what are some facts and patterns about economic uncertainty? Both macro and micro uncertainty appear to rise sharply in recessions and fall in booms. Uncertainty also varies heavily across countries—developing countries appear to have about one-third more macro uncertainty than developed countries. Second, why does uncertainty vary during business cycles? Third, do fluctuations in uncertainty affect behavior? Fourth, has higher uncertainty worsened the Great Recession and slowed the recovery? Much of this discussion is based on research on uncertainty from the last five years, reflecting the recent growth of the literature.

How adverse is the impact of fiscal policy uncertainty on economic and financial variables? To answer this question, we construct a novel cross-country database of news-based fiscal policy uncertainty indicators. Importantly, we track fiscal events that attract global attention, which we refer to as “global” fiscal policy uncertainty. We find that heightened fiscal policy uncertainty triggers contractionary effects, lowering industrial production in both advanced and emerging market economies. It also raises sovereign borrowing costs, generates synchronous movements in global financial variables including risk aversion, and strengthens the US dollar, even after accounting for US monetary policy shocks.

This paper evaluates the effects of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables representative of the US economy. Rather than estimating models at the same common low frequency, we use recently developed econometric models, which allow us to deal with data of different sampling frequencies. We find that credit and labor market variables react the most to uncertainty shocks in that they exhibit a prolonged negative response to such shocks. When looking at detailed investment subcategories, our estimates suggest that the most irreversible investment projects are the most affected by uncertainty shocks. We also find that the responses of macroeconomic variables to uncertainty shocks are relatively similar across single-frequency and mixed-frequency data models, suggesting that the temporal aggregation bias is not acute in this context.

China’s export benefits from the significant fiscal stimulus in the United States. This paper analyzes the global spillover effect of the American economy on China’s macro-economy using the Markov Chain Monte Carlo (MCMC)-Gibbs sampling approach, with the goal of improving the ability of China’s financial system to protect against foreign threats. This paper examines the theories of the consequences of uncertainty on macroeconomics first. Then, using medium-sized economic and financial data, the uncertainty index of the American and Chinese economies is built. In order to complete the test and analysis of the dynamic relationship between American economic uncertainty and China’s macro-economy, a Time Varying Parameter-Stochastic Volatility-Vector Autoregression (TVP- VAR) model with random volatility is constructed. The model is estimated using the Gibbs sampling method based on MCMC. For the empirical analysis, samples of China’s and the United States’ economic data from January 2001 to January 2022 were taken from the WIND database and the FRED database, respectively. The data reveal that there are typically fewer than 5 erroneous components in the most estimated parameters of the MCMC model, which suggests that the model’s sampling results are good. China’s pricing level reacted to the consequences of the unpredictability of the American economy by steadily declining, reaching its lowest point during the financial crisis in 2009, and then gradually diminishing. After 2012, the greatest probability density range of 68% is extremely wide and contains 0, indicating that the impact of economic uncertainty in the United States on China’s pricing level is no longer significant. China should therefore focus on creating a community of destiny by working with nations that have economic cooperation to lower systemic financial risks and guarantee the stability of the capital market.

This *.zip file contains the model output from ensemble simulations for the Lorenz 84-Stommel 61 model (hereafter L84-S61; Van Veen et al, 2001; Daron and Stainforth, 2013). To run these simulations, we used the E-forth ensemble generator (de Melo Viríssimo and Stainforth, in preparation), which is a MATLAB toolboox that allows for large ensembles of low-dimensional dynamical systems to be run and studied in a systematic way (de Melo Viríssimo and Stainforth, 2023).

These model outputs are presented and discussed in the Preprint "Micro and macro parametric uncertainty in climate change prediction: a large ensemble perspective". The manuscript describes the experiments performed, the parameter values used and the modifications done to the original L84-S61 model. For this matter, we also refer you to Daron and Stainforth (2013) and de Melo Viríssimo et al. (2024).

All files uploaded were generated from simulations run by the lead author.

For specific information about each file uploaded, please refer to the README file. The details of each experiment are also presented in the supplementary materials of the preprint above. If you have any questions, please feel free to contact me.

References:

Van Veen et al. (2001): https://onlinelibrary.wiley.com/doi/abs/10.1034/j.1600-0870.2001.00241.x

Daron and Stainforth (2013): https://dx.doi.org/10.1088/1748-9326/8/3/034021

de Melo Viríssimo and Stainforth (2023): https://doi.org/10.5194/egusphere-egu23-14755

de Melo Viríssimo et al. (2024): https://doi.org/10.1063/5.0180870

de Melo Viríssimo and Stainforth (in preparation): to appear

Graph and download economic data for Equity Market Volatility Tracker: Macroeconomic News And Outlook (EMVMACRONEWS) from Jan 1985 to May 2025 about volatility, uncertainty, equity, and USA.

Research data associated with the manuscript: [1] Górajski, M., Kuchta, Z., 2022, Designing Optimal Macroeconomic Policy Rules under Parameter Uncertainty: A Stochastic Dominance Approach.

This work is supported by the National Science Centre in Poland under Grant No. 2017/26/D/HS4/00942.

It contains all user-defined MATLAB and R functions that implement our algorithms and replicate all results. We group them into seven folders: 1. main_data It performs the data preparation process.

1. main_estimation It estimates 25 versions of the Erceg, Henderson, and Levine (2000) small-scale DSGE model (EHL model). They differ by the monetary policy rule. We consider eight Taylor-type rules (see Table 1) and one nominal GDP targeting rule (H.2) (see Appendix H).

2. main_measuring_uncertainty It evaluates the MWL and OPFC distributions for all versions of the EHL model.

3. main_compare_losses It contains the novel EP Bayesian tests for the SDk relations from Section 4.2. We use these tests to compare the MWLs.

4. main_robust_simple_rules It replicates all Bayesian and min-max robust strategies.

5. main_simulations It collects all codes that perform the simulations of the EHL model with SDk-optimal and estimated policy rules.

6. main_performance_BayesEP_SDk_tests It assesses the performance of the EP Bayesian tests for SDk relations.

Abstract In this paper, we offer a Bayesian decision-theoretic approach to policy evaluation in rational expectation models. First, we show how to correctly assess and rank simple policy rules under the welfare loss minimization criterion in the presence of uncertainty about the model's structural parameters. We consider a Bayesian policymaker that assesses the effectiveness of policy actions, by comparing the distributions of welfare losses using stochastic dominance orderings. Second, we propose a new Bayesian testing procedure to verify higher and infinite degrees of stochastic dominance. Third, we demonstrate a potential use of the suggested approach to a dynamic stochastic general equilibrium model, estimated for the U.S. economy. We show that using stochastic dominance to rank simple monetary policy rules yields different rankings than well-established robust approaches. The contemporaneous monetary policy rule that reacts to inflation and the output gap, with an interest rate smoothing mechanism, minimizes the welfare loss for all decision-makers who admit infinite degree stochastic dominance preferences.

This paper exploits a data rich environment to provide direct econometric estimates of time-varying macroeconomic uncertainty. 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. (JEL C53, D81, E32, G12, G35, L25)

We propose a nonrecursive identification scheme for uncertainty shocks that exploits breaks in the volatility of macroeconomic variables and is novel in the literature on uncertainty. This approach allows us to simultaneously address two major questions in the empirical literature: Is uncertainty a cause or effect of decline in economic activity? Does the relationship between uncertainty and economic activity change across macroeconomic regimes? Results based on a small-scale vector autoregression with US monthly data suggest that (i) uncertainty is an exogenous source of decline of economic activity, and (ii) the effects of uncertainty shocks amplify in periods of economic and financial turmoil.

This article investigates the macro-level drivers of adult-age language learning with a focus on migration based on a new dataset on German language learning in 77 countries (including Germany) for 1992-2006. Fixed-effects regressions show that language learning abroad is strongly associated with immigration from countries of the European Union and the Schengen Area whose citizens enjoy free access to Germany, while language learning in Germany is strongly associated with immigration from countries with restricted access. The different degrees of uncertainty about access to Germany seem to be of importance for preparatory language learning. To shed light on country heterogeneities, we substitute the location fixed effects with a vector of country characteristics, which include several distance measures among others, and we estimate a random-effects model. Last, we provide some tentative arguments in favour of a causal interpretation. The main results related to the role of uncertainty are mostly unaffected. The Skilled Immigration Act from 2020 removes this uncertainty with potential positive effects on preparatory language learning and economic and social integration.

Graph and download economic data for Economic Policy Uncertainty Index for United States (USEPUINDXD) from 1985-01-01 to 2025-06-23 about uncertainty, academic data, indexes, and USA.

We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by adding the how. The current forecasting literature has focused on matching specific variables and horizons with a particularly successful algorithm. To the contrary, we study the usefulness of the underlying features driving ML gains over standard macroeconometric methods. We distinguish four so-called features (nonlinearities, regularization, cross-validation, and alternative loss function) and study their behavior in both the data-rich and data-poor environments. To do so, we design experiments that allow to identify the treatment effects of interest. We conclude that (i) nonlinearity is the true game changer for macroeconomic prediction, (ii) the standard factor model remains the best regularization, (iii) K-fold cross-validation is the best practice, and (iv) the \( {L}_2 \) is preferred to the \( \overline{\epsilon} \)-insensitive in-sample loss. The forecasting gains of nonlinear techniques are associated with high macroeconomic uncertainty, financial stress and housing bubble bursts. Furthermore, ML nonlinearities are helpful when considering density forecasts.

This article investigates the impact and transmission of uncertainty regarding the future path of government finances on economic activity. Employing a data-rich approach, I introduce a novel proxy that captures uncertainty surrounding public finances, which I refer to as sovereign uncertainty. In an application to Spain, sovereign uncertainty shocks persistently dampen the economy in the medium-run, whereas macro-financial uncertainty shocks originating in the private sector induce a negative short-lived response in real activity. Additionally, a New Keynesian model rationalizes the empirical results, emphasizing the role of financial frictions and monetary policy decisions in transmitting the effects of sovereign uncertainty shocks.

This package contains the program codes and data files necessary to replicate
the results of the spillover analysis in

Economic Policy Uncertainty in the Euro Area:
Cross-country Spillovers and Macroeconomic Impact
By Volker Clausen, Alexander Schloesser and Christopher Thiem.

Please cite this paper if you use any of this material for your own research.
Also, please do not redistribute or circulate this package without the author's consent.

This report provides a macroeconomic framework to support the Jamaican Government's efforts to achieve macro stability, promote higher growth, and reduce poverty. It details the recent economic difficulties and discusses a mix of monetary and fiscal policies that could lower inflation. The recent economic performance of Jamaica has included definite progress in several areas (specifically foreign exchange liberalization, deregulation, and privatization). Unfortunately, the expansive monetary policy, based in government deficits, money supply growth, and wage increases, has led to higher inflation. The efficiency of long term investments has been hampered by economic uncertainty and high inflation as well as structural impediments. These include: modernizing the financial sector, improving the quality of the labor force and labor market functioning, providing critically needed infrastructure while improving the regulatory frameworks, improving the performance of the public sector, and unburdening the small business sector. The poverty situation is updated and shows that while the Government~^!!^s social programs have provided some support to the poor during 1991-1994, this has been offset by high inflation and low growth during that period. In the future, higher growth will be necessary to make a significant reduction in poverty.

This paper explores how changes in macroeconomic uncertainty have affected the decision to reply to the European Central Bank’s Survey of Professional Forecasters (ECB’s SPF). The results suggest that higher (lower) aggregate uncertainty increases (reduces) non-response to the survey. This effect is statistically and economically significant. Therefore, the assumption that individual ECB’s SPF data are missing at random may not be appropriate. Moreover, the forecasters that perceive more individual uncertainty seem to have a lower likelihood of replying to the survey. Consequently, measures of uncertainty computed from individual ECB’s SPF data could be biased downwards.