Where do high or low growth rates \ud come from and how do the mechanisms that underlie economic growth \ud work? This article is a PNAS Direct Submission. ↵#All growth rates in this study are compound annual percentage rates. Copyright © 2020 National Academy of Sciences. For example, we find that only 2 of 10 low-frequency forecasts for the low-income countries fall within 1 sample SD of a combined expert forecast and only 4 of 10 for China. This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. In the United States, GDP growth rates have been relatively good … The RCPs clearly understate the range of concentrations relative to projections that incorporate the uncertainty in productivity growth. Depending upon the magnitude of the uncertainties and the rate at which they are resolved, climate policies might need to be more or less stringent to meet international objectives. For the shorter time horizon, to mid-21st century, there is relatively little difference between the two methodologies in the IQR of the forecasts. Proceedings of the National Academy of Sciences, Earth, Atmospheric, and Planetary Sciences, https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=about, https://github.com/peterchristensen/GrowthForecastDistributions, www.pnas.org/lookup/suppl/doi:10.1073/pnas.1713628115/-/DCSupplemental, https://scholar.harvard.edu/barro/publications/barro-ursua-macroeconomic-data, globalchange.mit.edu/files/document/MITJPSPGC_Rpt125.pdf, Quantifying Uncertainty in Long-Run Forecasts, US racial inequality: A pandemic-scale problem, Journal Club: Machinery of heat shock protein suggests disease interventions. We recognize the shortcomings of GDP as a measure of output, but alternative measures are not available on a long historical timescale and are not used in long-run models (15). MIT JPSPGC Report 125. Before summarizing the major results, we emphasize the inherent difficulties of projecting trends of economic growth into the distant future because of the variety of time-varying forces at work and the potential for unanticipated events and technologies to have impact. A notable approach on which we draw is the work of Müller and Watson, or MW, which demonstrates that long-run trends in a range of time series processes can be captured by projecting the series onto a set of trigonometric functions (37, 38, 39). For global growth, the means are within 0.05% points for both methods and both horizons. In an environment with such a high degree of uncertainty, active management has become even more critical as dislocations and extreme panic can create opportunities but also cause indiscriminate market movements. Alternative measures of productivity include output per hour worked and total factor productivity, which measures output per weighted unit of capita and labor (and sometimes other inputs). But most forecasters expect growth to slow to about 1 to 1.5 percent, with some economists anticipating even weaker results. Â. Only 50% of the low-frequency forecasts for midcentury are higher than the full-century estimate (midcentury estimates are 0.16 percentage points higher on average). Uncertainty and Economic Growth. Panel data analysis based on a growth model, supplemented by variables to simulate transitional cycle, and performed on a sample of transition economies for the period 1995—2002, confirms that high levels of transition-specific uncertainty had a negative impact on economic growth. SSP data for SSPs are from IIASA (https://tntcat.iiasa.ac.at/SspDb/). Uncertainty has a negative impact on economic growth, directly through negatively affecting the effectiveness of R&D, and indirectly through reducing the level of openness of a country. Forecasts of long-run economic growth are critical inputs into policy decisions being made today on the economy and the environment. To obtain comparable SSPs, we take the reference SSPs that are generated by the modeling community and assume these generate 2100 CO2 concentrations according to the MAGICC model (SSP Public Database, version 1.1: https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=about). “Cross-Country Evidence on the Link Between Inflation Volatility and Growth,” Applied Economics , 30, 1998, pp. When uncertainty of the population growth, in comparison with its expectation, is sufficiently large, the growth rate of the technological progress and the capital … And the adverse economic (and health) consequences will continue to fall disproportionately on the most vulnerable sections of society. To make the WUI comparable across countries, the raw count is scaled by the total number of words in each report. Edited by William C. Clark, Harvard University, Cambridge, MA, and approved March 9, 2018 (received for review August 1, 2017). The primary finding is that the uncertainty in long-run growth is larger than assumed in widely used models of climate change. Results from this study suggest a greater than 35% probability that emissions concentrations will exceed those assumed in the most severe of the available climate change scenarios (RCP 8.5), illustrating particular importance for understanding extreme outcomes. Both approaches also indicate higher and more uncertain growth rates for China and low-income countries. Third, higher asset volatility magni–es the negative impact of uncertainty on growth. In fact, 97% of the responses across regions in the expert sample have the expert’s quantile estimate to 2050 higher than the estimate to 2100 (midcentury estimates are 0.56 percentage points higher on average). Economic uncertainty also appears to play an important role at the current juncture. Expert and low-frequency estimates by region and time horizon. ↵†Low-frequency forecasting refers to a method for modeling stochastic trends that vary on timescales greater than business cycle frequencies. All Rights Reserved. This may be particularly important when the sample is small relative to the forecast horizon and where there may be nonstationarities in the underlying processes. The Review is a journal specialized in and a premier outlet for scholarly research at the intersection of social values and economics, and encourages researchers engaged in high-quality work in these areas. Is such uncertainty a factor discouraging economic recovery? This finding indicates that models in which climate models treat RCP8.5 as an upper bound on future climate forcings exclude a range of concentrations that systematic economic projections indicate are reasonably likely. Available at, A stochastic model of the long-range financial status of the OASDI program (Social Security Administration, Woodlawn, MD), SSA Actuarial Report 117, The 2016 long-term budget outlook (Congressional Budget Office, Washington, DC), CBO Publication 51580, Testing models of low‐frequency variability, Low-frequency conometrics (National Bureau of Economic Research, Cambridge, MA), No. Online ISSN 1091-6490. The World Uncertainty Index covers 143 countries with populations of 2 million or more. We use expert forecasts from the Yale Long Run Growth Survey and a low-frequency statistical approach to produce systematic probabilistic estimates of long-run per-capita GDP growth over the 21st century, covering six regional groupings and two time horizons. Expert predictions have been utilized less formally to construct forecasts of long-run growth rates as part of larger climate modeling studies (24, 25). Image credit: Rosenzweig lab, Weizmann Institute of Science. [See the footnotes (*) for a list of survey respondents. Building on two centuries' experience, Taylor & Francis has grown rapidlyover the last two decades to become a leading international academic publisher.The Group publishes over 800 journals and over 1,800 new books each year, coveringa wide variety of subject areas and incorporating the journal imprints of Routledge,Carfax, Spon Press, Psychology Press, Martin Dunitz, and Taylor & Francis.Taylor & Francis is fully committed to the publication and dissemination of scholarly information of the highest quality, and today this remains the primary goal. Financial Development, Uncertainty and Economic Growth Financial Development, Uncertainty and Economic Growth Lensink, Robert 2004-10-09 00:00:00 DE ECONOMIST 149, NO. ©2000-2020 ITHAKA. This is mainly due to a deep sense of uncertainty concerning not only the trade disputes themselves, but also the prospects for economic growth, the high levels of debt, the underestimated levels of risk in financial markets, and political developments. This item is part of JSTOR collection At the upper end of the distribution, the experts refer in their qualitative responses to the possibility of an acceleration of technical change, including artificial intelligence and health technology, as most likely positive shocks to productivity growth in the 21st century. They also … impact on economic growth. To get a good handle on the role of uncertainty in economic growth, the IMF constructed a quarterly measure of uncertainty. But most forecasters expect growth to slow to about 1 to 1.5 percent, with some economists anticipating even weaker results. 3, 2001 FINANCIAL DEVELOPMENT, UNCERTAINTY AND ECONOMIC GROWTH** BY ROBERT LENSINK* Summary By performing a cross-country growth regression for the 1970-1998 period this … The difference between the two approaches is particularly dramatic for China. We constructed the World Uncertainty Index (WUI) – a quarterly index of uncertainty – for 143 individual countries from 1996 onwards. Low-frequency methods have not at this time been used for productivity growth outside the United States. This result holds for most regional stratifications, but most notably does not hold in the higher percentiles for low-income countries. Select the purchase In contrast to existing measure of econom… Structural methods represent another important approach for modeling productivity growth but to our knowledge have not been used formally to generate long-run forecasts of productivity growth. RCP8.5 was designed to represent “a very high baseline emissions scenario” and is intended to represent the upper bound of climate forcings available in the literature. The peer nomination process yielded a sample of economic experts that is widely recognized and that vary in field and methodological orientation.¶ Survey responses were provided by 16 survey respondents and 13 experts included complete forecasts distributions that were used to estimate the combined forecast distributions. These and many other authors find detrimental economic effects of monetary, fiscal, and regulatory policy uncertainty on growth and investment. Access supplemental materials and multimedia. option. Both the expert survey and the low-frequency statistical approach yield similar results for the median global economic growth rate: ∼2% per year from 2010 to 2100. We address this issue by fixing the quantiles of the distribution (which have natural coordinates) and asking experts to forecast productivity growth rates. Get PDF (3 MB) Abstract. Survey respondents were selected using a process of nomination by a panel of peers. Genetic insights could help shore up populations of a rare dog species thought to be nearly extinct in the wild. (See above.). Third, the findings show that national income per-capita, education, population, financial development and institutional quality all raise insurance premiums, while inflation lowers … Since inflation uncertainty and unemployment uncertainty are positively correlated, these empirical studies may be capturing in part the effect of uncertainty about future economic activity on output. Understanding structural uncertainty is a critical component of climate research and policy. growth model, supplemented by variables to simulate transitional cycle, and performed on a sample of transition economies for the period 1995-2002, confirms that high levels of transition-specific uncertainty had a negative impact on economic growth. Quantifying uncertainty in long-run economic growth has become fundamental to analysis of uncertainty in integrated assessment models and has been highlighted as a key priority by the Intergovernmental Panel on Climate Change and the National Academy of Sciences (3⇓–5). We compare the range of concentrations of the RCPs with those generated by the DICE model. It is therefore important for policymakers to ensure that economic policy uncertainty does not eventually slow down economic growth. Our results indicate that existing scenarios miss the upper tail of productivity growth, implicitly understating the likelihood of high output growth rates and the resulting high emissions, concentrations, temperature change, and climate damages. It is one of the most popular and debated topics in \ud economic science: economic growth. Both of these are at work in long-run (decadal or century-long) future growth rates. Author contributions: P.C., K.G., and W.N. The MW method uses both frequentist and Bayesian procedures to incorporate uncertainty. University of Illinois at Urbana–Champaign, Uncertainty in long-run forecasts of quantities such as per capita gross domestic product, Uncertain demographic futures and social security finances, Environmental economics. We find that an increase in economic policy uncertainty as measured by our index foreshadows a decline in economic growth and employment in the following months. Implications for social programs and policies may be discussed in regular articles or in a Speakers' Corner contribution. Cross-section regressions on growth suggest that after accounting for standard variables from the endogenous growth literature, policy uncertainty and growth are correlated. This study investigates the effects of public debt uncertainty on economic growth in 10 emerging European economies over 2000–2015 period. What does global expansion of higher education mean for the United States? Thank you for your interest in spreading the word on PNAS. NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. That is, if we cite growth between years t and T, or g(t,T), the growth rate is calculated as follows: g(t,T)= 100{[y(T)/y(t)]1/(T−t)−1}. designed research, performed research, contributed new reagents/analytic tools, analyzed data, and wrote the paper. 1 and Table 1 illustrate the projections of global annual per-capita output over the 2010–2100 period for both the expert survey and the low-frequency statistical approach. The present study focuses on gross domestic product (GDP) per capita, which has been shown to be numerically close to other measures over the long run and is most closely related to model assumptions in fields such as climate change. The long-run growth rate of the economic system is ultimately bounded in mean and its fluctuation of growth will not be faster than the polynomial growth. Image credit: Anang Dianto (photographer). We report the Bayesian estimates, which require fewer assumptions and are feasible to match to the exact quantiles from our expert forecasts. They hypothesize that when employers are unsure of future regulations, they postpone hiring and investment decisions rather than risk having to reverse them in the future. Check out using a credit card or bank account with. Available at, Comparing the point predictions and subjective probability distributions of professional forecasters, Forecasting economic and financial time-series with non-linear models, A comparison of linear and nonlinear univariate models for forecasting macroeconomic time series, Cointegration, Causality and Forecasting: A Festschrift for Clive, Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product, The MIT emissions prediction and policy analysis (EPPA) model: Version 4. 4 Health uncertainty vs. economic uncertainty: The need to safely restart growth The pandemic, the fallout, and a “shock and awe” policy response In what now feels like a distant memory, the US economy started 2020 on a positive note with the signing of a limited phase-one trade deal with China, leading to a revival in … (B) Projected CO2 concentrations in middle for 2100. uncertainty could lead to an abrupt economic decline whereas lower uncertainty does not necessarily rebound the economy from the recession. JSTOR®, the JSTOR logo, JPASS®, Artstor®, Reveal Digital™ and ITHAKA® are registered trademarks of ITHAKA. w21564, Measuring uncertainty about long-run predictions, The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century, Long-term economic growth projections in the shared socioeconomic pathways, The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: An overview, The representative concentration pathways: An overview. We consider several economic uncertainty indicators for the US and UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based economic policy uncertainty, twitter chatter about economic uncertainty, subjective uncertainty about future business growth, and disagreement among professional forecasters about future GDP growth. Two approaches have been used by researchers and government agencies to develop forecasts of long-run productivity growth: (i) time series estimation using historical data and (ii) statistical estimation using expert expectations.§ This study makes forecasts using both approaches and presents a systematic comparison of the results from both methods. The IQR for the low-frequency statistical approach over 2010–2100 is significantly lower (1.0 percentage point), with most of the difference coming from the 10th and 25th percentiles, as is shown in Fig. Financial Development, Uncertainty and Economic Growth Financial Development, Uncertainty and Economic Growth Lensink, Robert 2004-10-09 00:00:00 DE ECONOMIST 149, NO. The WUI is defined using the frequency of the word 'uncertainty' (and its variants) in the quarterly EIU country reports. This study also presents estimates of uncertainty in long-run growth forecasts, which are critical for modeling uncertainty in long-run physical and economic outcomes. The paper investigates the relationship between fundamental uncertainty, a recurrent theme in post-Keynesian economic literature, and economic performance in transition economies. Expert forecasts indicate that economic growth will follow historical trends over the next four decades but not across the entire century. Uncertainty and Growth Disasters. Projection lines for 2010–2100 show per-capita output from survey (blue lines) and low-frequency forecasts (black lines). We adjust MW prediction intervals to match the quantiles of the forecast distribution that were specified in our expert survey, and we extend the projections to 2100. It provides evidence on the correlation between policy uncertainty and per capita real GDP for 46 developing countries over the 1970-85 period. uncertainty around the economic outlook by publishing its forecasts for growth and inflation in the form of ‘fan charts’, rather than single-point forecasts. This assumption implies that uncertainty (measured, for example, as the SD of productivity shocks) declines with the square root of the time horizon. Based on research papers in Economics (RePEc) factor rankings, the overall peer-selected sample includes: 3 of the top 10 economists in any field, 2 of the top 5 development economists, 2 of the top 5 growth economists, 1 of the top 5 macroeconomists, 1 of the top 5 economic historians, and 1 of the top 5 forecasting economists. For over sixty-five years, the Review of Social Economy has published high-quality peer-reviewed work on the many relationships between social values and economics. Uncertainty in the transitional economic environment is enhanced by factors such as institutional transformation, political and social instability, and legacies of the past. 1317–26. Given the better economic performance in Q3, RBC Global Asset Management recently upgraded its 2020 growth forecasts for both the U.S. and Canada. The Congressional Budget Office requires estimates of uncertainty in long-run productivity growth forecasts to study the impact of uncertainty of productivity growth on revenues, expenses, and budget deficits. Second, the response of economic growth to an increase in uncertainty … Recent statistical approaches to quantify the long-run uncertainty of economic variables have focused on low-frequency dynamics. However, the SSPs are not based on probabilistic methods and are not structured to formally capture uncertainty in long-run productivity growth rates. Empirical studies that simultaneously include several indicators of economic conjuncture – such as the unemployment rate, the economic policy uncertainty index, the cost of public debt, and the consumer confidence index – do not explain all the decline in birth rates in Europe and the US in the period 2008 … This notably contrasts with the global estimates, for which we find greater uncertainty in the expert forecasts. In other words, uncertainty pushes individuals and corporations to act more conservatively, which could lead to lower overall economic consumption and growth, fewer debt issuances, and higher unemployment (Bloom, 2009; Caggiano, Castelnuovo, & Figueres, 2017; Kahle & Stulz, 2013). First, estimates from SSP2 are consistent with median estimates of the present forecasts. The issues addressed here (for climate change or demographic developments) require analysis of low-frequency variability—at the timescale of a decade or more. One of the most important findings of this analysis is that uncertainty in per-capita GDP growth rates in the present study is substantially higher than stochastic projections embedded in multiple existing public policy applications, with direct effects on regulations in the United States and other countries. They apply their approach using annual (1901–2014) and a post-World War II time series for the United States to construct a 75-y forecasts for per-capita GDP growth, inflation, and stock returns in the United States. ↵§In SI Appendix, we discuss these approaches in more detail. This paper studies the interactions between uncertainty, investment and economic growth. These surveys combine forecasts from multiple forecasters to develop aggregate predictions because combined forecasts have been shown to have a smaller forecast error (using the mean squared error) than individual forecasts (22, 23). “Policy Uncertainty, Persistence and Growth,” working paper W3848, National Bureau of Economic Research, 1991. Keywords: uncertainty, economic transition, institutions, economic growth INTRODUCTION Uncertainty in the context of historical time is one of the core elements of post-Keynesian economic theory (see Dow 1991: 204; Dow and Hillard 1995). Upon selection, the experts were contacted by email and provided with a link to the digital Qualtrics survey. The difference between the two approaches emphasizes the potential importance of nonstationarities in future growth patterns and the need to address potential discontinuities in long-run growth projections.   The correlation between the uncertainty index and growth is strong and clearly negative. By Jonathan H. Adler on December 3, 2011 9:55 am. Estimates from both methods indicate substantially higher uncertainty than is assumed in current studies of climate change … One advantage of utilizing information from expert forecasts in addition to extrapolating from historical data are that they can draw upon and appropriately weight numerous sources of information and account for new trends or other factors that may lead to breaks in trends. One common approach in climate policy analysis is based on economic growth rates defined as part of SSPs. Enter multiple addresses on separate lines or separate them with commas. Changing environmental conditions and genetic adaptations may explain how penguins radiated and expanded their geographic ranges to encompass diverse environments. ↵¶The criteria for nomination included contributions to the economic growth literature, familiarity with empirical research on medium-run and long-run growth, and diversity in regional expertise. (Participants were provided with information about historical per-capita GDP growth rates. Analysing the causal relationship between fluctuations in uncertainty and output growth is not straightforward as causality can be bi-directional: higher uncertainty affects economic activity, but (adverse) shocks to output are also likely to raise uncertainty. The findings here indicate that current research may be based on estimates that substantially underestimate uncertainty about output growth, particularly at the upper end (43, 44). Most work on variability of economic trends focuses on high-frequency dynamics, as with daily or monthly volatility of financial variables such as the stock market or business cycle frequency of output, wages, or inflation. ↵**“The SSP scenarios do not cover the full spectrum of plausible economic projections, but they do illustrate a substantial variance in global GDP levels by the end of the century” (41). Determining benefits and costs for future generations, Modeling uncertainty in climate change: A multi-model comparison (National Bureau of Economic Research, Cambridge, MA), Working Paper No. This work was partly supported by the Carnegie Commission of New York (W.N. The results show that CO2 concentrations are effectively unchanged when uncertainty is introduced in the other four parameters. By performing a cross-country growth regression for the 1970-1998 period this paper finds evidence for the fact that the impact of policy uncertainty on economic growth depends on the development of the financial sector.   The economists who do uncertainty research relate uncertainty and economic activity. See https://ideas.repec.org/top/. Second, the range of SSPs does not reflect the uncertainties in either the expert or the low-frequency forecasts. This highlights why is it vital … One of the most direct applications is projecting productivity growth to construct economic and geophysical models to project climate change and estimate the social cost of carbon estimates for rulemaking in the United States and around the world (2). Long-run growth scenarios are also imbedded in projections of greenhouse gas (GHG) emissions and concentrations as well as projections of temperature and other climatic outcomes (6, 7), thereby underpinning the full range of scientific research on the physical impacts (8⇓–10) and economic damages from climate change (11, 12). 1317–26. And the adverse economic (and health) consequences will continue to fall disproportionately on the most vulnerable sections of society. While extremely challenging, the effort to quantify uncertainty in long-run productivity growth is necessary for understanding central scientific uncertainties and forming a solid basis for key regulatory decisions in the United States and other countries. This finding has critical implications for the future development of a climate modeling program that is capable of addressing and incorporating uncertainty. Fig. All growth data are indexed by setting output in 2010 to 100. The results indicate that the projections from the low-frequency statistical approach may be less robust for low-income countries and may miss structural shifts that expert forecasts suggest are likely to occur in the second half of the 21st century. We implement the MW low-frequency forecasting methodology using time series data on per-capita global and regional growth rates for 1900–2010 using data from refs. 13 and 14.   The process of R&D can continue indefinitely if an economy is able to constantly reduce its coss by having access to a pool of general … These studies use discrete cosine transforms to estimate low-frequency variability for several economic variables and demonstrate that the low-frequency method provides robust predictions of uncertainty for multiple macroeconomic series over the past 100 y (39). We also find far greater uncertainty in economic growth in low-income countries in the low-frequency forecasts than the expert forecasts. For the 2010–2100 period, the 50th percentile growth forecast is 2.0% per year for the expert forecast and 2.2% per year for the low-frequency forecast. QnAs with Enquye Negash, Zeresenay Alemseged, and Jonathan Wynn. The combination of long-run time series techniques with expert forecasts allows for an analysis of areas of agreement and disagreement between these different methods, resulting in more robust forecasts. Al-Marhubi, Fahim. ), the Department of Energy (P.C., K.G., and W.N. ↵‖Surveys of short-run expectations of economic growth rates have sometimes elicited the probabilities associated with a given set of growth rates (for example, the probability of growth between 0% and 1%). These projections assume that productivity growth is characterized by finite-variance shocks that are independent and identically distributed (i.i.d.). “Cross-Country Evidence on the Link Between Inflation Volatility and Growth,” Applied Economics , 30, 1998, pp. On Technology, Uncertainty and Economic Growth . This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1713628115/-/DCSupplemental. For example, the 90th percentile over the 2010–2100 period indicates a growth rate in China of 12.7% per year using the low-frequency statistical approach and only 4.9% per year based on the expert surveys. These include investments in infrastructure as well as policies affecting public and private pension funds and social insurance (1). Projections and uncertainties about climate change in an era of minimal climate policies. Three responses did not include comprehensive sets of estimates and were omitted from the uncertainty study.]. We do not capture any email address. Terms-of-trade uncertainty and economic growth Enrique G. Mendoza * Department of Economics, Duke University, Durham, NC 27708, USA Received 4 September 1994; accepted 18 April 1996 Abstract This paper examines a stochastic endogenous growth model in which terms-of-trade uncertainty affects savings and growth. Exploring the influence of economic policy uncertainty on the relationship between tourism and economic growth with an MF-VAR model Han Liu, Ying Liu, and Yonglian Wang Tourism Economics 0 10.1177/1354816620921298 Expert surveys are widely used to develop “consensus” estimates of short-run forecasts (up to 3 y) of economic growth; they have become key inputs in financial research and monetary policy (21). It appears that a higher level of financial development partly mitigates the negative impact of policy uncertainty on economic growth. Projections of long-run productivity growth and economic growth are primary inputs into analyses used to support long-term planning and decision-making on many critical national priorities. The authors declare no conflict of interest. We also thank workshop participants at the Yale Workshop on Climate Change Uncertainty, the Stanford Energy Modeling Forum, the Conference on Global Economic Analysis, and Fondazione Eni Enrico Mattei for helpful comments. The survey first provided experts with historical data containing information on per-capita GDP growth rates for 1900–2010 using data from Maddison (26) Barro and Ursúa (27). On the impact of economic uncertainty index on the economy in the world can be summed up as macroeconomic, micro-finance, research shows that the epu index and economic growth index (GDP, PMI, industrial added value) has a negative correlation; the difference between the European and American epu index has a … ** Rather, they are used to describe “uncertainty in mitigation, adaptation, and impacts associated with alternative climate and socioeconomic futures” (16). The empirical analysis is conducted through both supply and demand side factors of bank credit growth … Available at, An overview of CMIP5 and the experiment design, CMIP5 scientific gaps and recommendations for CMIP6, Irreversible climate change due to carbon dioxide emissions, Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations, Climate change and Hurricane-like extratropical cyclones: Projections for North Atlantic polar lows and medicanes based on CMIP5 models, The structure of economic modeling of the potential impacts of climate change: Grafting gross underestimation of risk onto already narrow science models, Bayesian probabilistic population projections for all countries, A new scenario framework for climate change research: The concept of shared socioeconomic pathways, Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy, The Rise and Fall of American Growth: The U.S. Standard of Living Since the Civil War, Institutions as a fundamental cause of long-run growth. Global aggregates are geometric means of national growth rates, weighted by share of global income in 2006. The present results present an important upward revision in the uncertainty reflected in commonly used forecasts and demonstrates important implications for climate change. 26 and 27. GDP growth has been positive for nearly 6 years and, while global growth has slowed somewhat on the back of slower growth in key markets such as China and Brazil, global GDP is expected to expand at a modest pace over the near-term.2 Recent signs of a world economic slowdown can be seen in the global purchasing … For each region, we examine two forecast horizons: 2010–2050 and 2010–2100. (A) Forecast uncertainty for global output in 2100 from expert and low-frequency methods and SSPs. Global and regional growth rates are constructed using constant 2006 output shares. Projected CO2 concentrations for SSPs come from SSP public database, version 1.1, and RCPs at right, version 2.0, at IIASA (https://tntcat.iiasa.ac.at/SspDb/). Fig. We further study the implications of uncertainty in productivity growth via comparison with the RCPs, which are a set of scenarios developed by modelers to represent the full range of projected GHG concentrations in 2100 (42). Global conflict and civil unrest, persistent corruption or the deterioration of institutions, and sustained disruptions to world trade are cited as the most likely negative shocks to 21st-century growth. The Review provides a platform for established social-economics research, but also for research from other branches of economics and the social sciences, when the goal of developing better understandings of the role of social values in economic life is pursued. Data deposition: The data reported in this paper have been deposited in Github, https://github.com/peterchristensen/GrowthForecastDistributions. Table 1 provides estimates of the quantiles of the distribution of per-capita output growth for both time horizons and different regional aggregations. There are several reasons why uncertainty about future economic activity may reduce economic growth. In promoting discourse on social-economic themes, and unifying and invigorating scholarship around them, the journal is centrally concerned with these core research areas. The full set of global growth rates implied by the SSPs excludes most of the upper quartile of both of the forecast distributions, implying that the probability of high emissions and climate damages may be underestimated in current analyses based on the SSP scenarios. Our primary results suggest a median 2010–2100 global growth rate in per-capita gross domestic product of 2.1% per year, with a standard deviation (SD) of 1.1 percentage points, indicating substantially higher uncertainty than is implied in existing forecasts. The results reported in Table 1 indicate substantially higher uncertainty in long-run economic growth than has been assumed in climate–economy models, in IPCC assessment reports, and in a large body of science on the impacts of global climate change (4⇓⇓–7, 16, 25, 33). 1. Boyan Jovanovic and Sai Ma. 2A compares the per-capita GDP growth from expert and low-frequency forecast distributions (10th, 25th, 50th, 75th, and 90th percentiles) with the five reference (no policy) SSP scenarios of per-capita growth.†† The figure reveals two important findings. We rely on the DICE model for this comparison because it is simple to adopt, is widely used by analysts, and has results that are in the middle of a range of estimates of uncertainty in a multimodel study of integrated assessment models (see SI Appendix for detailed explanation). We thank Lint Barrage, Roger Cooke, Angus Deaton, Robert Gordon, Matthew Grant, Anil Kashyap, Nick Lardy, Robert Mendelsohn, Tony Smith, Michael Spence, T. N. Srinivasan, Larry Summers, Paul Sztorc, John Weyant, Kieran Walsh, and Mark Watson for excellent comments and invaluable assistance with various parts of this project. The SSPs are five scenarios that provide 100-y forecasts for key demographic and economic variables; they are designed to provide plausible “storylines” for the evolution of these variables (16, 39). Researchers reveal key details of how the heat shock protein mechanism disassembles the α-synuclein amyloids linked to Parkinson’s disease. Despite its importance, there is a sparse literature on long-run forecasts of economic growth and the uncertainty in such forecasts. SSP5, a high-growth baseline, falls closer to the 75th percentile of our two forecast distributions. Available at, Intergovernmental Panel on Climate Change, Fifth assessment report: Climate change 2014. Actual historical data and projections of global output, 1900–2100. The two approaches are also similar for the 75th and 90th percentiles. Participants were selected on the basis of the frequency of nomination. To capture the changes in the levels of transition-specific uncertainty, the authors have designed the uncertainty index, based on a weighted selection of Heritage Foundation and Freedom House data. SSP2 is described as a “middle of the road” scenario, with “medium” demographics, development of advanced energy technologies, frontier productivity growth, and regional convergence. These estimates are similar for the two methods used—the expert survey and the low-frequency statistical estimation approach—with a key difference being that expert judgment finds greater uncertainty and higher likelihood of lower economic growth in the second half of the 21st century. Terms-of-trade uncertainty and economic growth Enrique G. Mendoza * Department of Economics, Duke University, Durham, NC 27708, USA Received 4 September 1994; accepted 18 April 1996 Abstract This paper examines a stochastic endogenous growth model in which terms-of-trade uncertainty affects savings and growth. We directly compare the resulting forecast distributions for six groupings: World, United States, China, High-Income Countries, Middle-Income Countries, and Low-Income Countries. See SI Appendix for details on the survey instrument.) Furthermore, differences in the upper quartile of CO2 concentrations disappear in models with uncertainty in other key parameters but not in the productivity growth rate (see SI Appendix for multimodel and productivity-only results). We emphasize that these differences are driven almost entirely by uncertainty in productivity growth. Both methodologies suggest that growth rates will be higher during the first half of the 21st century than the second, although the expert survey suggests greater uncertainty over the longer run (to 2100). (Any bias in the forecasts from our expert information would reduce the uncertainty in reported forecast distributions, such that our findings should be interpreted as a lower bound on differences between the uncertainty in the expert forecast versus other estimates.). We especially thank the forecast respondents: Daron Acemoglu, Erik Brynjolfsson, Angus Deaton, Brad DeLong, Robert Gordon, Mun Ho, Peter Klenow, Benjamin Jones, Charles Jones, Nicholas Lardy, Lawrence Lau, Nebojsa Nakicenovic, John Reilly, Michael Spence, Nicholas Stern, and David Weil. ), and the National Science Foundation through the Network for Sustainable Climate Risk Management under National Science Foundation Cooperative Agreement GEO-1240507 (P.C., K.G., and W.N.). One group of economists created an Uncertainty Index based on words that relate to uncertainty and the economy in ten prominent newspapers. shocks. In the SSP storylines, economic growth rates vary based on structural factors that are assumed to determine productivity growth (40, 41). This study presents comprehensive probabilistic long-run projections of global and regional per-capita economic growth rates, comparing estimates from an expert survey and a low-frequency econometric approach. Papers published range from conceptual work on aligning economic institutions and policies with given ethical principles, to theoretical representations of individual behaviour that allow for both self-interested and 'pro-social' motives, and to original empirical work on persistent social issues such as poverty, inequality, and discrimination. Furthermore, the emissions and concentrations scenarios that underpin the study of climate change impacts, damages, and adaptation across a range of scientific domains do not reflect the range of economic growth trajectories determined by the present study, and most omit the upper end of the output distribution. Our results indicate that there is a greater than 35% probability that emissions concentrations will exceed those assumed in RCP8.5. Economic freedom and political stability had positive impact on economic growth, while economic policy uncertainty in the US had mixed impact on economic growth. A wide range of time series methods has been used to construct macroeconomic forecasts, typically focusing on high-frequency processes [the dynamics of growth and financial markets in business cycles (29⇓–31)]. Public policy research on a variety of topics relies upon forecasts of productivity growth. CO2 concentrations at left use output growth based on the estimates from the expert mean and dispersion, and then project 2100 concentrations using the DICE-2016R model. Request Permissions. Understanding the uncertainty in these forecasts is critical for decisions being made today, including infrastructure, investments in public and private pension funds, funding social insurance systems, and investments in mitigating and adapting to climate change. Our expert forecast data come from the Yale Long Run Growth Survey, which was designed to elicit predictions and uncertainties about the growth in per-capita GDP and was administered in 2014–2015. For terms and use, please refer to our Terms and Conditions Estimates from both methods indicate substantially higher uncertainty … This study develops estimates of uncertainty in projections of global and regional per-capita economic growth rates through 2100, comparing estimates from expert forecasts and an econometric approach designed to analyze long-run trends and variability. As Powell this week prepares to address the Fed’s annual central bankers’ conference – usually held in Jackson Hole, Wyoming, but being conducted virtually this year because of the ongoing COVID-19 pandemic – uncertainty and the threat it poses to economic growth looms larger than ever.
2020 uncertainty and economic growth