Is finance a veil? Lead‐and‐lag relationship between financial and business cycles: The case of China

Abstract

This study examines the lead‐and‐lag relationship between financial cycles (FCs) and business cycles (BCs) by using Chinese provincial data. We construct FCs of the financial sector on the basis of three financial variables: credit‐to‐GDP (gross domestic product) ratios, house prices, and equity prices. We use the panel dynamic logit model to investigate the lead‐and‐lag effect between two sectors. Results show that each province has its own unique FCs and BCs. Hence, financial policies should be different in dissimilar provinces. Next, we find that FCs lead BCs and not vice versa. Furthermore, the leading effect is stronger in rich provinces than in poor areas.

Financial Cycles in the Economy and in Economic Research: A Case Study in China

“…A possible explanation for this might be that the government in China sets the economic and financial plan every five years. Hence, policy plays a significant role in China's economics (Shen et al, 2019).…”

“…Initially, we determine the proxy indicators on financial cycles in the real economy. It is widely recognized that financial cycles cannot be identified and characterized without credit, house prices and asset prices (Shen et al, 2019). Meanwhile, the proxy indicators for financial cycles assessment are also relevant to financial recessions, i.e., the depressions that coincide with banking crises (Jordà et al, 2013;Schüler et al, 2020).…”

“…Some argue that financial cycles are intrinsic to business cycles (Borio, 2017). However, in contrast with business cycles, recessions concerned with financial disruptions are deeper and long-lasting (Shen et al, 2019). For this reason, an intensive debate on the concept and nature of financial cycles sprang up from researchers and policymakers (Lee et al, 2017).…”

Regional business cycles in emerging economies: a review of the literature

“…(2020), besides applying the above mentioned methodologies, use a 2-stage least squares (2SLS) to test the robustness of estimates. Shen et al. (2019) also calculate the economic and financial cycles in Chinese regions and determine the co-movements by adopting a dynamic panel logit model to estimating the relationship of lead-lag between two cycles.…”

“…That is the reason why Luo et al (2020), besides applying the above mentioned methodologies, use a 2stage least squares (2SLS) to test the robustness of estimates. Shen et al (2019) also calculate the economic and financial cycles in Chinese regions and determine the co-movements by adopting a dynamic panel logit model to estimating the relationship of lead-lag between two cycles. Lastly, Mej ıa-Reyes and D ıaz-Carreño (2016), studying the Mexican regions, estimate the co-movement between the manufacturing GDP and public spending through OLS and autoregressive spatial models.…”