Long-run Trends Research Articles

Long-run trends in partisan polarization of climate policy-relevant attitudes across countries

ABSTRACT We summarize long-run trends in partisan polarization of voters’ climate policy-relevant attitudes across 36 countries and multiple decades (1993–2020). We find substantial growth in partisan polarization of these attitudes in the US, other Anglophone countries and much of Western Europe, but not elsewhere. Comparing Western European to Anglophone countries, partisan polarization is more prominent on different climate policy-relevant attitudes, and primarily involves supporters of different party types. Observed partisan polarization patterns are not well explained by changes in either linkage to economic ideology or levels of general societal disagreement on climate policy-relevant questions. Growing partisan polarization does not generally reflect all partisan groups becoming more accepting of climate reform yet diverging because of differing rates of change. Instead, what disagreements there are on these matters have become increasingly tied to party support. Our findings highlight the increasing difficulty of achieving sustained political consensus for effective climate reform across many countries.

Understanding the Influence of Wind and Solar PV on Socioeconomic and Environmental Trends: A Non-causality Perspective

This paper investigates the non-causality perspective of economic growth, investment, social well-being, employment, GHG emissions on renewable energy sources (RES) (wind and solar PV), providing a comprehensive overview of renewable technologies that effect on socio-economic and environmental drivers. The analysis and enhancing linear regression techniques, addressing cross-country RES installed capacity heterogeneity, and applying time-lags techniques to better understand the temporal effect of RES´s investment. The study tested: I. economic growth in a country is related to the development of RESs, employment, investment. II. Increased RESs share positively impacts social well-being. III. RESs implementation reduces GHG emissions. Our findings suggest that RES positively influenced economic growth over time for countries with higher installed capacity. However, this statistically significant is not observed across countries with lower installed capacity nor across all indicators, like social well-being, employment, investment, which show modest growth trend over time. GHG emissions also showed an inverse trend, suggesting the needs the renewable electricity´s expansion accompanied by additional mitigation measures to reduce emissions. One limitation is the temporal restriction, which limits the assessment of long-run trends. Future research should focus on gathering a larger dataset for long-run trends analysis.

Reciprocal Deposits and the Banking Turmoil of 2023

Reciprocal deposits are deposits exchanged between banks to effectively increase deposit insurance coverage. Their use grew significantly during the banking turmoil of 2023. This Economic Commentary describes what they are, their connection to brokered deposits, how their legal treatment has changed over time, and which banks use them the most. It also discusses longer-run trends in uninsured deposits.

The convergence of total-factor energy efficiency across Chinese cities: A distribution dynamics approach

Improving energy efficiency is considered the most direct route to reducing carbon emissions on a massive scale. To examine the long-run trend of China's energy efficiency, this paper employs a distribution dynamics approach to analyze the convergence of total-factor energy efficiency (TFEE) across 286 Chinese cities between 2002 and 2014. The result suggests the existence of convergence, which comes more from the efficiency declines in the high TFEE cities rather than the efficiency gains in the low TFEE cities. Despite the fact that a few cities have performed well in energy efficiency, the majority of cities have converged to a low-efficiency point. Further analyses show that the inefficiency was attributed to inefficient energy use in small- and medium-sized cities. Our analysis provides strong scientific support for China's ongoing energy conservation and environmental protection policies.

Flexible markov-switching models with evolving regime-specific parameters: an application to Brazilian business cycles

ABSTRACT This article develops a flexible class of Markov-switching models in which the GDP growth rate is decomposed into a long-run growth trend and evolving regime-dependent means. The models can account for multiple regimes, breaks in the long-run trend, stochastic volatility, and time-varying transition probabilities. They can also handle data outliers that may arise from rare events, such as the COVID-19 crisis. We illustrate our methodology by modelling Brazilian GDP growth, which has exhibited complicated dynamics over the past four decades. Our results suggest two regimes, one long-run trend break, significant time variation in volatility, and the presence of outliers. Moreover, the selected model features time-varying transition probabilities driven by domestic variables (fiscal stance, reserves, and the real interest rate). Significantly, our findings indicate a marked decline in Brazil’s long-run growth in recent years.

Monetary Policy and the Long-Run Trend of Treasury Yields

Monetary Policy and the Long-Run Trend of Treasury Yields

Determinants of global neutral interest rates

We provide a comprehensive account of the determinants of global longer-run neutral interest rates—the real component of policy interest rates consistent with both economic activity and inflation at their longer-run trends. Using a cross-country model for 11 advanced economies in the 1960–2019 period, we simultaneously account for productivity, demographics, global supply of safe assets, demand factors for safe assets, and global spillovers faced by each economy from the rest of the world’s developments. We find two main results: safe asset supply is a major determinant of neutral rates, with its positive contribution since 2008 counteracting negative contributions from many other determinants, and global spillovers are important determinants of neutral rates’ trajectories and co-movements.

Do Changes in Risk Perception Predict Systemic Banking Crises?

This paper examines if incorporating changes in financial market risk perception improves the predictive power of an early-warning system for systemic banking crises. In explaining systemic banking crises, the existing literature identifies inflating stock and real estate bubbles, credit booms, and surges in net capital inflows as the common drivers. Employing panel logit models to predict the postwar systemic banking crises in advanced economies to occur within three–four years, the paper’s key finding is that, even after controlling for the effects of surges in asset and credit markets and net capital inflows that are above the long-run trends for an extended period, market participants’ increasing underestimation of downside risks is a significant predictor of these crises. Incorporating changes in risk perception improves the prediction accuracy of the model significantly. This finding is robust across alternative prediction horizons, systemic crisis definitions, and risk-perception measures. Consistent with the recent theoretical developments in the form of the diagnostic expectations hypothesis for financial markets, the interpretation is that recent recurring good news about financial markets and the broader economic trends for sufficiently long periods lead to growing neglect of tail risks and riskier financial transactions, raising systemic risk and the likelihood of a financial crisis. The finding suggests monitoring financial market risk perception, in addition to the conventional indicators, to predict and avert systemic banking crises.

21st century progress in computing

In the search for explanations for slower productivity growth since the mid-2000s in many countries, one possibility is a slower pace of progress in digital technologies. In this paper we show that the cost of computation has continued to decline rapidly, taking into account innovation in chip types and cloud computing. This is a continuation of its long-run trend; the decline has slowed since 2010, but not earlier. As firms use computational power along with other inputs including relevant human and organisational capital, to the extent that the productivity slowdown is linked to technology use the explanation is likely to lie in these other elements of the input bundle.

Forecasting Day-Ahead Brent Crude Oil Prices Using Hybrid Combinations of Time Series Models

Crude oil price forecasting is an important research area in the international bulk commodity market. However, as risk factors diversify, price movements exhibit more complex nonlinear behavior. Hence, this study provides a comprehensive analysis of forecasting Brent crude oil prices by comparing various hybrid combinations of linear and nonlinear time series models. To this end, first, the logarithmic transformation is used to stabilize the variance of the crude oil prices time series; second, the original time series of log crude oil prices is decomposed into two new subseries, such as a long-run trend series and a stochastic series, using the Hodrick–Prescott filter; and third, two linear and two nonlinear time series models are considered to forecast the decomposed subseries. Finally, the forecast results for each subseries are combined to obtain the final day-ahead forecast result. The proposed modeling framework is applied to daily Brent spot prices from 1 January 2013 to 27 December 2022. Six different accuracy metrics, pictorial analysis, and a statistical test are performed to verify the proposed methodology’s performance. The experimental results (accuracy measures, pictorial analysis, and statistical test) show the efficiency and accuracy of the proposed hybrid forecasting methodology. Additionally, our forecasting results are comparatively better than the benchmark models. Finally, we believe that the proposed forecasting method can be used for other complex financial time data to obtain highly efficient and accurate forecasts.

Dynamic Autoregressive Liquidity (DArLiQ)

We introduce a new class of semiparametric dynamic autoregressive models for the Amihud illiquidity measure, which captures both the long-run trend in the illiquidity series with a nonparametric component and the short-run dynamics with an autoregressive component. We develop a generalized method of moments (GMM) estimator based on conditional moment restrictions and an efficient semiparametric maximum likelihood (ML) estimator based on an iid assumption. We derive large sample properties for our estimators. Finally, we demonstrate the model fitting performance and its empirical relevance on an application. We investigate how the different components of the illiquidity process obtained from our model relate to the stock market risk premium using data on the S&P 500 stock market index.

The evolution of commercial finance in Ming-Qing China: 16th to Early-20th Centuries

Objective/Context: This article surveys the evolution of commercial finance in Ming-Qing China and responds to the debates about the role of finance in the “Great Divergence” between China and Europe. Methodology: Based on new historical materials, especially commercial documents, we study the evolution of financial organizations at different levels as delineated by Fernand Braudel. We also analyze the long-run trends of commercial interest rates in the Ming-Qing eras based on a novel historical database of interest rates in China. Originality: This article explores capital market developments since the 16th century and their relationship with the state —a topic that has been almost entirely neglected in the existing literature. We also find improvements in market integration in China before the late 19th century when Western financial institutions began to enter China, and the prime commercial interest rate in the capital market was much lower than the dominant accounts in the “Great Divergence” debate. Conclusions: While current comparative studies either emphasize the financial stagnation of Ming-Qing China relative to the West or emphasize its special development through non-market mechanisms, e.g., clans, this article shows that the capital market played a similar key role in the evolution of finance in Ming-Qing China as it did in advanced parts of Europe. Thus, we suggest that the difference in financial development between China and the West lies in the organizational structure of the financial sector and the relationship between finance and the state.

Dynamics of Industrial Electricity Demand in the State of Bahia (Brazil): Evolution of Price and Income and COVID-19 Implications

The growth in demand for electricity is a determining factor for the regional development. This research aimed to estimate the price and income elasticity parameters of the industrial demand for electricity in the State of Bahia, Brazil, from January 2003 to June 2022, in addition to making forecasts for the period from July to December 2022. After verifying that some of the analyzed data were non-stationary, we chose to use the cointegration method, estimating the econometric model through the Error Correction Mechanism (ECM). The ECM considers the model’s variables and their lags, relating the series’ short and long-run trends. The estimated parameters were inelastic and presented the following values: 0.501 and 0.762 (price and income, long-run) and 0.482 and 0.702 (price and income, short-run). The adjustment coefficient between the short and long-run was also statistically significant and indicated that approximately 8% of the difference between the effective value and the long-run value (balance value) is corrected in each period, demonstrating the rigidity of the consumption structure of electricity in the industrial sector in Bahia. The model also demonstrated an 8.1% reduction in consumption during COVID-19 incidence period. Regarding the forecasts, they proved to be robust and with an average difference of 5.4% in relation to what actually happened in the months of July and August 2022. Thus, the calculated parameters are configured as another source of information for public policymakers and private investors interested in the electricity sector in the State of Bahia.

Fragmented or Unified? The State of China’s Carbon Emission Trading Market

China has adopted a gradualism principle in establishing its carbon emission trading system from the regional pilot markets to a national one. In view of the huge market potential and large differences across China, this paper applies the cointegration test and VECM (Vector Error Correction Model) to investigate the long-run trends and the price dynamics of regional pilot markets. The results show that the prices of the regional pilot markets form three long-run trends exhibit mean-reversion patterns. The launch of the national market marks the different performance of regional pilot markets. After the launch of the national market, the number of long-run trends reduces from three to one and the severity of the mean-reversion patterns is eased, indicating the efficiency improvement in China’s carbon market from a fragmented toward a unified market. The policy implication is that China should further develop its national market by incorporating the regional markets into the national one and encouraging more market participants for market transaction.

Interview with Professor Kalevi Holsti: Brief Reflections on the Discipline of International Relations and World Problems

The long-run trend in the decline of interstate war is notable. Once a common feature of all civilizations and geographical areas, the world since 1945 has featured a very low probability that two or more states would resolve their conflicting interests by armed conflict. The probability that in any given year war between states will occur has declined to less than one percent. This pattern contrasts with the prevalence of domestic violence since 1945. Wars within states have made up the vast majority of armed conflicts, but our models of International Politics have little to say about them. But the benign International situation of the post Cold War era has begun to crumble. The Russian attack on the Ukraine, tensions over Taiwan, the lapse of arms control agreements, the arms build-up of China and India are indicators of increased dangers and greater probabilities of armed conflicts between states. Cyber wars, as between Israel and Iran, have also appeared. The certainties of the Cold War era have been replaced by uncertainties and higher risks.

Price Dynamics and Interactions between the Chinese and European Carbon Emission Trading Markets

The European carbon emission trading market is the largest and most mature market, while China’s carbon market has a short history. Institutionally, cross-market transaction is infeasible between the two markets. This paper investigates the long-run trend between the two markets as well as the price dynamics. Results show that a long-run trend exists between the Chinese and European carbon markets. Both markets possess self-correction capability in reducing price deviations, signaling a certain level of market efficiency. However, both markets also exhibit pricing inefficiency as historical price movements are able to impact prices. The European market informationally leads the Chinese market. Policy implications are that China should further upgrade its information disclosure system, such as unifying information disclosure standards across industries, and further develop its carbon derivatives markets to improve market transparency and market competition.

New insights into trends and reasons for the gender pay gap in Urban China, 1988-2013

ABSTRACT This study documents long-run trends of the gender pay gap (GPG) in urban China 1988–2013 using the Chinese Household Income Project microdata. We find a fluctuating and enlarging GPG over time. The average ratio of female to male earnings fell from 85.2% to 79.9%. Analysis by earnings percentiles shows that the GPG is larger at the bottom of the earnings distribution than it is at the top. We utilize OLS regressions, Blinder-Oaxaca decomposition, and Juhn-Murphy-Pierce decomposition to make a comprehensive analysis of the contributing factors to the GPG. By 2013, conventional human capital variables explained little of the GPG. Gender differences in location (ownership, occupation, and industry) were important, although the magnitude of the effect of three factors has changed over time. Gender differences in job characteristics (contract type and firm size) are also important in explaining the GPG. The increases in the unexplained gap contributed to the divergence of the gender gap. Analysis by sub-periods shows that there were distinctive patterns behind the changes of the GPG. The main contributors to the diverging trend of the GPG were changes in the wage structure to women and women’s disadvantages in unobserved skills.

Price and Income Elasticity of Residential Electricity Demand in the State of Bahia: 2004 to 2021

The main objective of this research is to estimate the price and income parameters of the residential electric power demand of Bahia state, Brazil. For this, monthly data from 2004 to 2021 is used. The consumption is analyzed in terms of the electricity price, income, number of residentials, rainfall, average temperature, and residential index price. Regarding climatic variables, despite being important for the study of the electricity sector, especially rainfall, since Brazil depends on water sources, they are rarely used. After verifying that part of the series is non-stationary, it is decided to use the method of Cointegration and Error Correction Mechanism (ECM). This estimator considers the model variables and their lags, reconciling short-run and long-run trends. The results are consistent with the established hypotheses, proving to be inelastic both in the short and long run. The parameters calculated can serve as another source of information, both for the agents responsible for conducting energy planning in the State of Bahia, and for eventual investors in the private sector.

Long-Run Trends and Cycles in Us House Prices

Long-Run Trends and Cycles in Us House Prices

Post-disaster tourism development and scenario planning for the quality of life of residents

Desarrollo del turismo post-catástrofe y planificación de escenarios Para la calidad de vida de los residentesResumenPropósitoEste estudio tiene por objetivo explorar la influencia del desarrollo del turismo post-catástrofe en la calidad de vida (CdV) objetiva de los residentes del condado de Wenchuan, simular la tendencia a largo plazo del desarrollo del turismo tras la catástrofe y la CdV basándose en tres escenarios políticos propuestos, y formular algunas sugerencias prácticas para promover el desarrollo del turismo sostenible.o.Diseño/metodología/enfoqueEste estudio utiliza el enfoque de dinámica de sistemas para desarrollar un modelo de dinámica de sistemas denominado “turismo-economía-medioambiente-vida” (TEMV) utilizando cuatro subsistemas: “el subsistema económico”, “el subsistema turístico”, “el subsistema medioambiental” y “el subsistema de vida”.ConclusionesLos resultados muestran que la influencia del desarrollo del turismo post-catástrofe en la CdV objetiva es compleja. Basándose en la teoría de Butler sobre el ciclo de vida del destino, la influencia del turismo post-catástrofe en la CdV objetiva presenta un cambio no lineal estrechamente vinculado a las etapas de desarrollo de los destinos turísticos. Se demuestra que el índice de CdV aumentó después de una disminución inicial en la primera etapa (2009-2013) y luego disminuyó en la etapa posterior (2013-2019). Las simulaciones de TEMV basadas en tres escenarios diferentes muestran que la actual trayectoria de desarrollo del turismo no es ideal. El escenario de sinergia, que destaca la importancia del desarrollo armonioso del TEMV, es el escenario óptimo.Originalidad/valorEste estudio llena la brecha existente en la literatura sobre la influencia del desarrollo del turismo post-catástrofe en la calidad de vida (CdV) objetiva desde la perspectiva de la dinámica de sistemas. La modelización del desarrollo turístico y la CdV objetiva contribuirá a una comprensión integral de si el desarrollo turístico puede mejorar, y cómo, la CdV de los residentes en las zonas afectadas por catástrofes