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This study aimed to know 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 from 2004 to 2020. In this study, the author uses term spread as the dependent variable that reflects macroeconomic risk. The cross-sectional risk comprises financial friction (FF), cash flow (CF), debt–service ratio, and stock market volatility as independent variables. By using the Autoregressive Distributed Lag (ARDL) Model method, this study shows that business-specific and stock market risk can 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 (CCI), money supply (M0), and Indonesia’s trade balance (TB).

Inquiries, commissions, reviews and the promise of broader data collection about racial and gender disparities are now the reflex defensive responses from state institutions charged with grievous social harm, particularly in the UK. Recommendations from these exercises are rarely implemented. As criminologists, our ability to produce and analyse data that evidences or better illuminates social harm has long been a key offer of the discipline to activism.

How are we to respond to the very institutions activist criminologists seek to challenge immediately offering this very activity, invariably protracted and ineffectual, as a reflex response to activist challenge? This chapter explores this tension. Grounded in the work of groups struggling to end police stop and search, it considers the strategy impasse around research and data production that faces grassroots activists and their accomplice researchers. The chapter proposes new routes for collaboration and action across activist and criminologist communities that may help move past the ‘data trap’. In short, it seeks to answer: do activists need more evidence?