<![CDATA[This study systematically reviews the literature on the ability of sectoral stock indices to predict sectoral economic growth, particularly using mixed-frequency forecasting approaches in emerging markets. The issue is important because stock markets operate at high frequencies (daily or weekly), while sectoral economic indicators—such as industrial output, sectoral GDP, and production indices—are typically available at lower frequencies (monthly, quarterly, or annually). This mismatch creates both methodological challenges and analytical opportunities in integrating financial and real-sector data. Using a systematic literature review, the study synthesizes theories of market efficiency, the relationship between finance and economic growth, and the Mixed Data Sampling (MIDAS) approach. The literature indicates that stock prices may contain forward-looking information related to profit expectations, sectoral demand, financing conditions, and investor sentiment. However, empirical evidence at the sectoral level in emerging markets remains mixed due to differences in market structures, macroeconomic volatility, uneven liquidity, and data limitations.The study concludes that integrating sectoral stock indices with economic indicators through mixed-frequency models offers valuable contributions to macro-financial forecasting, although further sector-specific and country-specific empirical research is still needed.. Keywords: sectoral stock indices; economic growth, mixed-frequency, MIDAS; emerging markets; forecasting; macro-financial.]]>
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