Saturday, January 31, 2026
From a paper by Neeraj Nautiyal, Mobeen Ur Rehman, Rami Zeitun, and Xuan Vinh Vo:
“We investigate how socially responsible investment (SRI) funds respond to different oil-induced price shocks, using Ready’s (2018) approach. Using daily data for six SRI indices from March 8, 2016, to November 29, 2024, we apply wavelet coherence and nonlinear causality methods to analyze the time-frequency relationship between oil shocks and SRI fund performance across different market states. Our findings reveal that supply and risk shocks play a significant role in driving the co-movement between oil price dynamics and SRI funds’ behavior returns, particularly at medium and lower frequencies, respectively. Risk shocks exhibit a systemic influence, consistently dominating supply and demand shocks, especially in the pre-2021 period and during the COVID-19 pandemic, though their effects fizzle out in stable market conditions. Quantile causality estimates confirm the strong predictive power of risk shocks, particularly at lower quantiles. Our work presents practical implications for ethical investors, dealing with oil-related market risks.”
From a paper by Neeraj Nautiyal, Mobeen Ur Rehman, Rami Zeitun, and Xuan Vinh Vo:
“We investigate how socially responsible investment (SRI) funds respond to different oil-induced price shocks, using Ready’s (2018) approach. Using daily data for six SRI indices from March 8, 2016, to November 29, 2024, we apply wavelet coherence and nonlinear causality methods to analyze the time-frequency relationship between oil shocks and SRI fund performance across different market states.
Posted by at 12:22 PM
Labels: Energy & Climate Change
From a paper by Cars Hommes, and Sebastian Poledna:
“This study investigates the potential of agent-based modelling to forecast economic crises, addressing the failure of standard macroeconomic models to predict the 2008 financial crisis and capture crisis dynamics. While dynamic stochastic general equilibrium models have incorporated financial frictions, solving them typically requires linearisation around steady states, which suppresses the non-linear feedback loops through which crises emerge. Agent-based models avoid this limitation by numerically simulating heterogeneous agents, preserving non-linear dynamics without approximation. We develop such an agent-based model for the euro area and show that out-of-sample forecasts outperform benchmarks. We further demonstrate that the model can forecast economic crises without exogenous shocks and accurately reproduce crisis dynamics. The model endogenously predicts the onset of the Great Recession, explains the persistence of the sovereign debt crisis, and reproduces the sharp contraction and swift recovery of the COVID-19 recession. The findings suggest that preserving non-linear feedback loops is essential for crisis prediction.”
From a paper by Cars Hommes, and Sebastian Poledna:
“This study investigates the potential of agent-based modelling to forecast economic crises, addressing the failure of standard macroeconomic models to predict the 2008 financial crisis and capture crisis dynamics. While dynamic stochastic general equilibrium models have incorporated financial frictions, solving them typically requires linearisation around steady states, which suppresses the non-linear feedback loops through which crises emerge. Agent-based models avoid this limitation by numerically simulating heterogeneous agents,
Posted by at 12:21 PM
Labels: Forecasting Forum
From a paper by Tayebeh Chaman, Ali Asghar Salem, Abbas Shakeri Hossein Abad, and Teymour Mohammadi:
“The inflation targeting regime, by emphasizing transparency, accountability, and anchoring inflation expectations, leads to improved inflation control, a reduction in economic instability, and the creation of a favorable environment for economic growth, productive investment, and lower income inequality. Therefore, the objective of the present study is to investigate the role of inflation targeting in income distribution across a sample of 39 countries, including 7 inflation-targeting and 32 non-inflation-targeting countries, using a difference-in-differences approach over the period 1995–2023. The findings indicate that the implementation of an inflation-targeting regime has a negative and statistically significant effect on the Gini coefficient, thereby reducing income inequality in the treatment-group countries relative to the control group. In addition, per capita GDP, the share of the agricultural sector in GDP, and foreign direct investment have negative and significant effects on income inequality, while the trade share of GDP has a positive and significant effect. Overall, the results suggest that adopting an inflation-targeting regime in countries experiencing high inflation and ineffective monetary policy frameworks can mitigate the adverse effects of inflation on income distribution. Thus, it is recommended that central banks in such countries implement an inflation-targeting framework to enhance macroeconomic stability, promote investment, and reduce income inequality.”
From a paper by Tayebeh Chaman, Ali Asghar Salem, Abbas Shakeri Hossein Abad, and Teymour Mohammadi:
“The inflation targeting regime, by emphasizing transparency, accountability, and anchoring inflation expectations, leads to improved inflation control, a reduction in economic instability, and the creation of a favorable environment for economic growth, productive investment, and lower income inequality. Therefore, the objective of the present study is to investigate the role of inflation targeting in income distribution across a sample of 39 countries,
Posted by at 12:19 PM
Labels: Inclusive Growth
Working papers and conferences:
On China:
On Australia and New Zealand:
On other countries:
Working papers and conferences:
On China:
Posted by at 5:00 AM
Labels: Global Housing Watch
Friday, January 30, 2026
On prices, rent, and mortgage:
On sales, permits, starts, and supply:
On other developments:
On prices, rent, and mortgage:
Posted by at 5:00 AM
Labels: Global Housing Watch
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