Graph and download economic data for Economic Policy Uncertainty Index for United States (USEPUINDXM) from Jan 1985 to Mar 2025 about uncertainty, academic data, indexes, and USA.

United States Business Uncertainty: Employment Growth: Smoothed data was reported at 0.055 % in Sep 2020. This records an increase from the previous number of 0.054 % for Aug 2020. United States Business Uncertainty: Employment Growth: Smoothed data is updated monthly, averaging 0.041 % from Jan 2015 (Median) to Sep 2020, with 69 observations. The data reached an all-time high of 0.060 % in Jun 2020 and a record low of 0.036 % in Mar 2019. United States Business Uncertainty: Employment Growth: Smoothed data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S018: Business Uncertainty Index.

United States Business Uncertainty: Sales Revenue Growth: Smoothed data was reported at 0.048 % in Sep 2020. This records a decrease from the previous number of 0.051 % for Aug 2020. United States Business Uncertainty: Sales Revenue Growth: Smoothed data is updated monthly, averaging 0.029 % from Jan 2015 (Median) to Sep 2020, with 69 observations. The data reached an all-time high of 0.055 % in May 2020 and a record low of 0.024 % in Apr 2016. United States Business Uncertainty: Sales Revenue Growth: Smoothed data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S018: Business Uncertainty Index.

Economic Policy Uncertainty for United States was 256.81000 Index in July of 2025, according to the United States Federal Reserve. Historically, Economic Policy Uncertainty for United States reached a record high of 1026.38000 in January of 2024 and a record low of 3.32000 in August of 2015. Trading Economics provides the current actual value, an historical data chart and related indicators for Economic Policy Uncertainty for United States - last updated from the United States Federal Reserve on July of 2025.

United States Business Uncertainty: Sales Revenue Growth: Unsmoothed data was reported at 0.045 % in Sep 2020. This records a decrease from the previous number of 0.052 % for Aug 2020. United States Business Uncertainty: Sales Revenue Growth: Unsmoothed data is updated monthly, averaging 0.028 % from Sep 2016 (Median) to Sep 2020, with 49 observations. The data reached an all-time high of 0.059 % in Mar 2020 and a record low of 0.019 % in Jan 2020. United States Business Uncertainty: Sales Revenue Growth: Unsmoothed data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S018: Business Uncertainty Index.

Graph and download economic data for Global Economic Policy Uncertainty Index: Current Price Adjusted GDP (GEPUCURRENT) from Jan 1997 to May 2025 about uncertainty, adjusted, GDP, indexes, and price.

United States Business Uncertainty: Employment Growth: Unsmoothed data was reported at 0.054 % in Sep 2020. This records a decrease from the previous number of 0.059 % for Aug 2020. United States Business Uncertainty: Employment Growth: Unsmoothed data is updated monthly, averaging 0.040 % from Sep 2016 (Median) to Sep 2020, with 49 observations. The data reached an all-time high of 0.065 % in May 2020 and a record low of 0.035 % in Jan 2019. United States Business Uncertainty: Employment Growth: Unsmoothed data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S018: Business Uncertainty Index.

Graph and download economic data for Business Uncertainty: Sales Revenue Growth (ATLSBUSRGUP) from Dec 2016 to Jun 2025 about growth, uncertainty, revenue, projection, business, sales, indexes, and USA.

United States Business Expectations: Sales Revenue Growth: Smoothed data was reported at 0.021 % in Sep 2020. This records an increase from the previous number of 0.014 % for Aug 2020. United States Business Expectations: Sales Revenue Growth: Smoothed data is updated monthly, averaging 0.035 % from Jan 2015 (Median) to Sep 2020, with 69 observations. The data reached an all-time high of 0.052 % in Jul 2018 and a record low of -0.010 % in May 2020. United States Business Expectations: Sales Revenue Growth: Smoothed data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S018: Business Uncertainty Index.

United States Business Expectations: Sales Revenue Growth: Unsmoothed data was reported at 0.025 % in Sep 2020. This records an increase from the previous number of 0.010 % for Aug 2020. United States Business Expectations: Sales Revenue Growth: Unsmoothed data is updated monthly, averaging 0.042 % from Sep 2016 (Median) to Sep 2020, with 49 observations. The data reached an all-time high of 0.060 % in Jul 2018 and a record low of -0.028 % in Apr 2020. United States Business Expectations: Sales Revenue Growth: Unsmoothed data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S018: Business Uncertainty Index.

Investor uncertainty, nicknamed "the fear index," tracks the VIX-CBOE Volatility Index, which measures the prices of various call and put options for the S&P 500. A higher value represents greater uncertainty in the future price of the S&P 500. Annual totals represent an equally weighted average of the monthly mean value of the index, calculated as the average of the adjusted close for every trading day during a particular month. Data is sourced from the Chicago Board Options Exchange.

United States Business Expectations: Employment Growth: Smoothed data was reported at 0.015 % in Sep 2020. This records a decrease from the previous number of 0.023 % for Aug 2020. United States Business Expectations: Employment Growth: Smoothed data is updated monthly, averaging 0.012 % from Jan 2015 (Median) to Sep 2020, with 69 observations. The data reached an all-time high of 0.023 % in May 2018 and a record low of 0.005 % in Apr 2020. United States Business Expectations: Employment Growth: Smoothed data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S018: Business Uncertainty Index.

This paper analyzes the performance of the monthly economic policy uncertainty (EPU) index in predicting recessionary regimes of the (quarterly) U.S. GDP. In this regard, the authors apply a mixed-frequency Markov-switching vector autoregressive (MF-MSVAR) model, and compare its in-sample and out-of-sample forecasting performances to those of a Markov-switching vector autoregressive model (MS-VAR, where the EPU is averaged over the months to produce quarterly values) and a Markov-switching autoregressive (MS-AR) model. The results show that the MF-MS-VAR fits the different recession regimes, and provides out-of-sample forecasts of recession probabilities which are more accurate than those derived from the MS-VAR and MS-AR models. The results highlight the importance of using high-frequency values of the EPU, and not averaging them to obtain quarterly values, when forecasting recessionary regimes for the U.S. economy.

United States Realized Sales Revenue Growth data was reported at 3.228 % in Apr 2025. This records an increase from the previous number of 2.407 % for Mar 2025. United States Realized Sales Revenue Growth data is updated monthly, averaging 4.450 % from Sep 2016 (Median) to Apr 2025, with 104 observations. The data reached an all-time high of 13.646 % in Jun 2021 and a record low of -9.952 % in Jun 2020. United States Realized Sales Revenue Growth data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S015: Business Uncertainty Index.

Graph and download economic data for Business Uncertainty: Employment Growth (ATLSBUEGUP) from Dec 2016 to May 2025 about growth, uncertainty, projection, business, employment, indexes, and USA.

This study initially analyses the connectedness among five indexes representing five asset classes: equities, bonds, commodities, currencies, and housing prices. Subsequently, it analyses the influence of policy uncertainty and equity market risk on the total connectedness of assets and their impact on the significance of the home price index. A time-varying parameter vector autoregressions (TVP-VAR) model has been employed to explore the connectedness of the assets. Secondly, quantile regression is employed to gauge the impact of uncertainty and market risk in this study. The findings show that the S&P500 is the market’s most influential index. The home price index has proven sensitive to shocks from government bonds, commodities, and stock indexes across the period analyzed. Finally, findings have indicated that policy uncertainty positively influences the overall connectedness among the variables at all the quantiles. Moreover, at higher quantiles, an increase in policy uncertainty and equity-market risk decreases the net connectedness of the house price index. These findings hold significant implications for investors and policymakers in terms of diversification of portfolios and mitigating portfolio risk during periods of economic turbulence. This study demonstrates the dynamic interrelationships among five major asset classes and indicates that policy uncertainty and equity market risk significantly influence asset connectivity. Employing TVP-VAR and Bayesian quantile regression, it reveals that the S&P 500 exerts dominant market influence, whereas the house price index exhibits significant sensitivity to shocks. The results highlight the significance of uncertainty for increasing interconnectedness, providing essential insights for investors and policymakers about risk management and portfolio diversification.

I am hereby sharing the dataset used in the paper titled 'Beyond Tradition: A Hybrid Model Unveiling News Impact on Exchange Rates'. The dataset comprises the following components: Taylor Rule Fundamentals: - Inflation - Industrial production index (as a high-frequency proxy of GDP) - Money market rate spanning from 2000 to 2018. Textual Information: - Economic Policy Uncertainty Index from https://www.policyuncertainty.com/index.html (as of November 9, 2023). - Time series of entropies calculated for U.S. Dollar-related news topics extracted from the Nexis-Uni database. Note: To acquire the textual data from the Nexis-Uni database, we conducted the following steps: We entered "U.S. Dollar" as a keyword in the search for news, resulting in over 15 million non-duplicate news items. Subsequently, we cleaned the news data and selected relevant news items using the following criteria: (i) The U.S. Dollar appears in the title of news items, (ii) The term "U.S. Dollar" is repeated several times in the news, (iii) The first paragraph of the news contains the word "U.S. Dollar", (iv) The news items are automatically selected by the Nexis-Uni database with the U.S. Dollar as the subject. Subsequently, we identified the topics related to the US Dollar from the news using LDA and calculated the Shannon entropies over time for each topic.

United States Realized Sales Growth: 25th Percentile data was reported at -0.331 % in Apr 2025. This records a decrease from the previous number of 0.000 % for Mar 2025. United States Realized Sales Growth: 25th Percentile data is updated monthly, averaging 0.000 % from Sep 2016 (Median) to Apr 2025, with 104 observations. The data reached an all-time high of 3.440 % in Sep 2021 and a record low of -16.216 % in Nov 2020. United States Realized Sales Growth: 25th Percentile data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.S015: Business Uncertainty Index.

The paper explores the role of business models in the link between uncertainty and bank risk. From the perspective of banks, given that future outcomes tend to be less predictable if banking uncertainty rises, we highlight a framework that a larger dispersion of bank shocks to bank-specific variables might mirror such decreased predictability as a consequence of increasing uncertainty. To compensate for the persistence of bank risk and address the endogeneity issue, we applied the system generalized method of moments (GMM) estimator as the main regressions. Analyzing a panel of commercial banks from Vietnam between 2007 and 2019, we find that higher levels of banking uncertainty may increase bank risk, as gauged by banks’ credit risk (loan loss reverses and non-performing loans) and default risk (Z-score index). This detrimental influence of uncertainty appears to be most pronounced with banks relying on pure lending, and it decreases with more non-interest income. A deeper investigation after estimating the marginal effects with plots reveals an asymmetric pattern that bank risk is immune to uncertainty in banks with the highest level of income diversification. Interestingly, we also provide evidence that uncertainty may lower the default risk level when income diversification exceeds a sufficiently high level. Our findings demonstrate that diversified business models are an efficient buffer against higher bank risk in times of increased uncertainty.

The paper explores the role of business models in the link between uncertainty and bank risk. From the perspective of banks, given that future outcomes tend to be less predictable if banking uncertainty rises, we highlight a framework that a larger dispersion of bank shocks to bank-specific variables might mirror such decreased predictability as a consequence of increasing uncertainty. To compensate for the persistence of bank risk and address the endogeneity issue, we applied the system generalized method of moments (GMM) estimator as the main regressions. Analyzing a panel of commercial banks from Vietnam between 2007 and 2019, we find that higher levels of banking uncertainty may increase bank risk, as gauged by banks’ credit risk (loan loss reverses and non-performing loans) and default risk (Z-score index). This detrimental influence of uncertainty appears to be most pronounced with banks relying on pure lending, and it decreases with more non-interest income. A deeper investigation after estimating the marginal effects with plots reveals an asymmetric pattern that bank risk is immune to uncertainty in banks with the highest level of income diversification. Interestingly, we also provide evidence that uncertainty may lower the default risk level when income diversification exceeds a sufficiently high level. Our findings demonstrate that diversified business models are an efficient buffer against higher bank risk in times of increased uncertainty.