In May 2025, a data error in the UK’s inflation release offered a rare case to study how markets respond to incorrect economic news and its later correction. On 21 May 2025, the ONS announced that consumer price index (CPI) inflation had jumped to 3.5% in April, up sharply from 2.6% in March. This headline figure overshot market expectations (consensus ~3.3%) and even the Bank of England’s forecast (~3.4%), signaling a surprise uptick in price pressures.

The United Kingdom’s official statistical system was shaken by revelations that critical economic data had been calculated using incorrect inputs, leading to inaccuracies in key indicators. The Office for National Statistics (ONS) – the UK’s national statistical agency – uncovered a methodological error in the price data used for GDP calculations, raising concerns that GDP growth figures for recent years were off-target.

Global trade liberalization has been a driving force in shaping economic outcomes over the past decade. Between 2017 and 2025, countries experienced significant changes in trade policy –making this period ideal for studying the impact of liberalization. In this analysis, we construct a comprehensive country-level panel dataset to examine how reducing trade barriers affects trade flows, GDP growth, and employment.

This framework outlines a comprehensive approach to analyzing global trade liberalization from 2017 to the present. It covers the key datasets needed (with sources), suitable econometric models, data preparation steps, and solutions for missing data and comparability issues.

The period from 2017 to 2024 has been tumultuous for global trade. After decades of steady liberalization, a wave of protectionism and trade tensions emerged, epitomized by tariff wars and rising barriers. At the same time, many countries pushed forward with new trade agreements and reforms to keep markets open.

Australia faces a pivotal choice in crafting its future low-carbon energy strategy: whether to pursue nuclear power, double down on solar energy, or some combination of both. This report provides a rigorous political and economic comparison of nuclear and solar energy options for Australia

This article investigates algorithmic decay—the degradation of model and strategy performance over time—in economics and finance. Using panel regressions with time-varying coefficients, structural break tests, Kalman filters, survival analysis, concept drift detection, and difference-in-differences methods, it demonstrates that algorithmic models experience statistically significant decay if not adapted. Empirical results across macroeconomic forecasting, financial trading, and behavioral interventions confirm decay’s prevalence and quantify its economic costs. Adaptive strategies, such as drift detection and model retraining, substantially mitigate decay. The paper argues that recognizing and managing algorithmic decay should become standard practice in economic modeling, similar to handling heteroskedasticity or autocorrelation.

This report compares housing-market dynamics, affordability trends, and policy responses in Canada, Australia, the United Kingdom, and the United States over 1995–2025. It integrates original econometric evidence—hedonic price regressions, cointegration/error-correction models, VAR impulse analyses, quasi-experimental policy evaluations, and spatial spill-over estimates—built on OECD, IMF, national-statistical, Zillow and CoreLogic datasets.

Over the past two centuries, tariff policies have shifted from high protectionism to widespread liberalization. Early tariffs supported industrial growth, but the Smoot-Hawley Tariff (1930) worsened the Great Depression, leading to post-WWII reductions under GATT. By the late 20th century, tariffs in advanced economies fell to historic lows, driving global trade expansion. While occasional trade wars and protectionist measures persist, historical trends show that lower tariffs have been key to economic growth and global integration.

This report provides a comprehensive econometric analysis of tariffs over the past 200 years, examining their historical evolution, impact on global trade, consumer sentiment, inflation, and sectoral dynamics. Key case studies include the role of tariffs in industrialization, the Smoot-Hawley Tariff’s impact during the Great Depression, modern trade conflicts like the U.S.-China trade war, and sector-specific effects on industries such as manufacturing, agriculture, and automotive. The analysis integrates historical data, econometric models, and empirical findings to quantify the costs and benefits of tariffs in capitalist economies.