Financial cycle, business cycle, and policy uncertainty in India: An empirical investigation

Paramanik, Rajendra Narayan; Bhandari, Avishek; Kamaiah, Bandi

doi:10.1111/boer.12320

Cited by 4 publications

(1 citation statement)

References 41 publications

(48 reference statements)

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“…Existing studies thus use Granger causality (Muradoglu et al ., 2000; Foresti, 2006; Pradhan et al ., 2015; Tekin and Yener, 2019; Paramanik et al ., 2022), vector autoregressive model (Pradhan et al ., 2015) and error correction model (Paramati and Gupta, 2011) to study the linkages of stock markets with economic growth. We contribute by using the ARDL modeling approach to obtain out-of-sample predictions of economic growth using sectoral stock market returns.…”

Section: Literature Reviewmentioning

confidence: 99%

The financial market's ability to forecast economic growth: information from sectoral movements

Marfatia

2023

JES

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PurposeFinancial market holds superior information that can give insights into the future trajectory of economic growth. Further, identifying sectors that hold the key to future economic growth is important for all economies, but particularly relevant to emerging markets. However, unlike existing studies, the paper provides new insights into the forward-oriented nexus between financial markets and economic growth.Design/methodology/approachThis paper takes a forward-looking approach of using financial market information to predict future economic growth. The authors use ARDL modeling approach to predict economic growth using the information from stock market sectoral returns.FindingsThe authors find that sectoral stock returns significantly improve economic growth forecasts. However, the forecasting superiority is not uniform across sectors and horizons. Auto, consumers' spending, materials and realty sectors provide the most forecasting gains. In contrast, banking, capital goods and industrial sectors provide superior forecasts, but only at horizons beyond one year. The authors also find that the forecast superiority of sectors at longer horizons is inversely related to volatility.Research limitations/implicationsResearch highlights the need for sector-focused policy actions in driving economic growth. Further, the findings of the paper identify sectors that drive short-, medium- and long-term economic growth.Practical implicationsThere is a significant heterogeneity among different sectors and across horizons in predicting economic growth. Results suggest that targeted policy actions in sectors like materials, metals, oil and gas, and realty are key in driving economic growth. Further, policies geared toward the grassroots industries are at least as beneficial as the large-scale industries. Evidence also suggests the need for an active fiscal policy to address infrastructural bottlenecks in primary industries like basic materials and energy. Evidence nevertheless does not undermine the role of monetary policy actions.Originality/valueUnlike any paper till date, the innovation of the paper is that it takes an ARDL modeling approach to measure stock market sectoral returns' ability to forecast economic growth several months ahead in the future. Though the paper considers the Indian case, the innovation and contribution extents to the entire field of economic studies.

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