Distribution Of GDP Growth Research Articles

China's GDP at risk: The role of housing prices

This paper studies the impact of house prices on the distribution of GDP growth in China (the 5th, median, and 95th percentiles). We show that house price appre-ciation positively affects future GDP growth, with a more significant impact on the tail outcomes - GDP at risk. Moreover, we find that housing bust is associated with GDP growth vulnerability; a sharp decline in house prices generates severe economic downturns. Our finding is supported by the investment channel, a housing boom stim-ulates investment, which boosts GDP growth. However, the subsequent housing bust suppresses investment, leading to increased downside risks to GDP growth.

The term effect of financial cycle variables on GDP growth

We study how current financial cycle variables (house prices, credit-to-GDP, and share prices) influence the entire distribution of future GDP growth. Changes in financial cycle variables affect borrowers’ and lenders’ balance sheets, resulting in the lower quantile of GDP growth to be more sensitive to the financial accelerator, while the upper quantiles are relatively stable over horizons. We also find the combination of the rapid growth in asset prices and higher leverage amplifies the effect of asset prices on the downside of GDP growth. Moreover, we rely upon financial cycles constructed using two popular methods to investigate the impact on the distribution of GDP growth. The findings are consistent with the impact of financial cycle variables. In addition, we execute a series of robustness tests and find that the results survive. Our results suggest that policymakers should consider the risk-return tradeoff between economic growth and financial stability in the term structure emanating from macro-financial linkages. Specifically, policies regarding credit expansion and contraction combined with the regulation of house and equity prices should be calibrated to the state of GDP growth.

The social architecture of capitalism

A dynamic model of the social relations between workers and capitalists is introduced. The model self-organises into a dynamic equilibrium with statistical properties that are in close qualitative and in many cases quantitative agreement with a broad range of known empirical distributions of developed capitalism, including the power-law firm size distribution, the Laplace firm and GDP growth distribution, the lognormal firm demises distribution, the exponential recession duration distribution, the lognormal–Pareto income distribution, and the gamma-like firm rate-of-profit distribution. Normally these distributions are studied in isolation, but this model unifies and connects them within a single causal framework. The model also generates business cycle phenomena, including fluctuating wage and profit shares in national income about values consistent with empirical studies. The generation of an approximately lognormal–Pareto income distribution and an exponential–Pareto wealth distribution demonstrates that the power-law regime of the income distribution can be explained by an additive process on a power-law network that models the social relation between employers and employees organised in firms, rather than a multiplicative process that models returns to investment in financial markets. A testable consequence of the model is the conjecture that the rate-of-profit distribution is consistent with a parameter-mix of a ratio of normal variates with means and variances that depend on a firm size parameter that is distributed according to a power-law.