Penelitian ini dilakukan dengan tujuan untuk mengetahui pengaruh cross-sectional risk, yang merupakan risiko spesifik bisnis dan volatilitas pasar saham, sebagai variabel untuk mengestimasi risiko makroekonomi di Indonesia. Penelitian ini mengobservasi perusahaan- perusahaan publik di Indonesia dan data-data makroekonomi Indonesia pada periode 2004-2020. Dalam penelitian ini, penulis menggunakan term spread sebagai variabel dependen yang merefleksikan risiko makroekonomi, dan financial friction, arus kas, debt-service-ratio, dan volatilitas pasar saham sebagai variabel independen. Dengan menggunakan metode Autoregressive Distributed Lag Model, penelitian ini menunjukkan bahwa risiko perusahaan secara spesifik dan risiko pasar saham mampu mengestimasi risiko makroekonomi, sehingga menjadi sinyal awal shock ekonomi, seperti resesi atau inflasi tinggi di masa depan. Model dalam penelitian ini juga meneliti hubungan cross-sectional risk terhadap indikator makroekonomi lainnya, seperti consumer confidence index, money supply, dan neraca dagang Indonesia. Setiap variabel merepresentasikan makna masing-masing dalam menjelaskan risiko makroekonomi Indonesia. Hasil penelitian ini diharapkan dapat memberikan wawasan kepada peneliti selanjutnya, investor, pelaku bisnis, perbankan, dan regulator.

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This study was conducted with the aim of knowing the effect of cross-sectional risk, which comprises business-specific risk and stock market volatility, as a variable for estimating macroeconomic risk in Indonesia. This study observes public companies in Indonesia and Indonesian macroeconomic data in the period 2004-2020. In this study, the authors use term spread as the dependent variable that reflects macroeconomic risk, and the cross-sectional risk comprises financial friction, cash flow, debt-service-ratio, and stock market volatility as independent variables. By using the Autoregressive Distributed Lag Model method, this study shows that business-specific risk and stock market risk are able to estimate macroeconomic risk, so that it becomes an early signal of economic shock, such as recession or high inflation in the future. The model in this study also examines the cross-sectional risk relationship with other macroeconomic indicators, such as the consumer confidence index, money supply, and Indonesia's trade balance. Each variable represents its own meaning in explaining Indonesia's macroeconomic risk. The results of this study are expected to provide insight to further researchers, investors, entrepreneurs, banks, and regulators.