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Does Supply or Demand Drive the Credit Cycle? Evidence from Central, Eastern, and Southeastern Europe
... Model 1 does not include any other assumptions and does not use any a priori information on demand and supply regimes, therefore it is quite difficult to implement and is subject to stability issues, as also witnessed by us and other authors. Interestingly, in this setting the price mechanism collapses and there is no way for the price to endogenously react to changes in demand or supply -the price level becomes exogenous, as noted by Maddala and Nelson (1974) and Everaert et al. (2015). ...
... In contrast, the credit market was characterised by an excess supply, driven by foreign banks flooding the domestic market with cheap and abundant external financing, that also contributed to relatively low domestic lending rates (see Kuodis and Ramanauskas, 2009;Karmelavičius et al., 2022). This finding is in line with the results of Everaert et al. (2015), who use a single-market credit disequilibrium model to identify imbalances in the overall credit market. For the boom period, their model highlights that credit supply factors dominated the pace of credit expansion in Lithuania. ...
During the Covid-19 pandemic, house prices and mortgage credit are growing at a long-unseen pace. However, it is unclear, whether such growth is warranted by the underlying market and macroeconomic fundamentals. This paper offers a new structural two-market disequilibrium model that can be estimated using full-information methods, and applied to analyse housing and credit dynamics. Dealing with econometric specification uncertainty, we estimate a large ensemble of the two-market disequilibrium model specifications for Lithuanian monthly data. Using the model estimates, we identify the historical drivers of Lithuania’s housing and credit demand and supply, as well as price and market quantity variables. The paper provides a novel approach in the financial stability literature to jointly measure house price overvaluation and mortgage credit flow gaps. We find that by mid-2021 Lithuania was experiencing a heating in housing and mortgage credit markets, with home prices overvalued by around 16% and the volume of mortgage credit flow being 20% above its fundamentals.
... (Gozgor, 2014); (Everaert et al., 2015); (Rabab'ah, 2015). However, they revealed countryspecific variances, and empirical investigations on their impact show comparable conclusions compatible with economic theory. ...
Inspired by the desire to take a unique trajectory with the greater goal of new knowledge addition, this study examined the moderating effect of digitalization on the triangular relationship between digitalization, banks’ credit to private sector and economic growth in Nigeria for 2009 – 2021. The highly debatable direction of the relationship between credit to the private sector and economic growth in Nigeria has remained unresolved; by throwing digitalization in the mix, this study seeks to ascertain if there is a substantial shift in the direction of the subsisting argument with refence to Nigeria. The Autoregressive Distributed Lag (ARDL) approach was applied due to the mixed order of integration results obtained from the Unit Roots Test, which accounted for some structural breaks. For this study, the long-run results carry more prominence than the short-run since there is inherent room for adjustments. The empirical results show that private sector credit has a positive and significant impact on economic growth in Nigeria in the short run. However, in the long run, credit to private sector has a positive and insignificant impact on economic growth in Nigeria. The results also revealed that ddigitalization does not moderate the effect of banks' credit to the private sector on economic growth in Nigeria for the period reviewed. Because of the strategic role of financial intermediation played by deposit money banks, the paper supports the ongoing efforts of the Central Bank of Nigeria (CBN) in deepening the integration of digitalization into the financial services sector.
This paper investigates the factors that affect loan growth in state-owned banks in Bangladesh. We collected data from 2012 – 2022. Our examination finds that loan growth in state-owned banks depends on several industry-dependent variables i.e. size, liquidity, efficiency, non-performing loans, etc. The influence of bank size, income, liquidity, non-performing loan ratio, and cost-to-income ratio is the main emphasis of this study's investigation into the factors influencing bank lending. According to the statistics, there is a significant positive correlation between size and lending. Bank liquidity and lending show a strong negative correlation. The study also found higher lending is associated with higher non-performing loans with marginal statistical significance. The efficiency ratio shows a substantial negative impact on lending. We apply OLS primarily followed by FE estimation. To check the validity of the regression models of the study, we take several diagnostic tests. To improve bank performance and stability, policymakers and bank management may benefit greatly from these results.
The subject of the research refers to the impact of bank loans on the private sector on the GDP growth rate per capita. Due to the possibility of a feedback relationship between economic growth and credit activity, the models were evaluated with the method of ordinary least squares (OLS) and with the generalized method of moments (GMM). The obtained results are entirely consistent, statistically significant, and well-adjusted. However, the endogeneity test in the GMM model shows that the variables for which a feedback relationship is assumed are exogenous. The growth of bank loans to the private sector has a statistically significant and positive impact on the GDP growth rate per capita. According to the evaluated asymmetric model, the coefficient in conditions of accelerated economic growth is 0.63. Bank loans to the private sector and the growth rate of GDP per capita have a non-linear relationship, in the form of an inverse U-curve, with a turning point of about 34% of GDP.
In an emerging market economy (EME) that depends largely on bank-credit, it is important to decipher whether supply-side or demand-side factors are responsible for a sluggish credit growth phase. A formal empirical analysis using Indian data and a disequilibrium model suggests that demand side factors have majorly contributed to the credit slowdown during the post-GFC period and prior to the pandemic. This could be because of adequate supply of funds, and several concerted policy actions taken by the regulatory authorities to mitigate concerns over the asset quality risks. In contrast, lower investment demand and global supply side bottlenecks have often contributed to demand side weaknesses, suggesting the need for strong policy support to uphold credit demand.
The credit-driven housing net worth channel has been identified as a determinant of the sharp drop in US employment between 2007 and 2009. We examine the impact of this channel on the labour market in the EU using panel data for 20 countries covering the period 1996 to 2017. This period saw substantial changes in both credit provision and labour market performance in the EU. The full sample results show changes in housing net wealth having a significant influence on total employment and its traded and non-traded components, with a one per cent change in housing net wealth being associated with about a 0.2 per cent change in total employment. Coefficient values are larger when changes in non-traded employment are the dependent variable, while the wealth effect is greater when negative housing net wealth shocks occur. In contrast to the US evidence, we find significant wage responses to housing net worth shocks arising in the EU.
I use panel data on 20 countries to analyze the links between savings (defined as time deposits and savings accounts) and credit extended by banks. Credit growth is not related to prior changes in savings, at least not in the short run. This result indicates that the intuition behind the loanable funds theory does not work well in explaining macroeconomic dynamics. I also find that the share of savings in total deposits decreases during credit booms. The existence of such an effect is predicted by the Austrian business cycle theory. Based on the above results, I infer that an important disadvantage of fractional-reserve banking is a tendency for the market interest rate to diverge from the natural interest rate.
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