Publications

Timely monitoring of the housing market developments in Lithuania is one of the key elements in the analysis framework of the macroprudential authority aiming to contribute to financial stability in Lithuania. In this paper, we addressed three important questions related to Lithuanian house prices, namely, whether house prices are under- or over valuated, which explanatory variables have the biggest impact on the growth of house prices and what the future development of the Lithuanian house price index could be. Three separate modelling and forecasting exercises were performed in order to tackle these questions. The first exercise employs the vector error correction modelling (VECM) approach to assess under- or overvaluation of the house prices. We then use an autoregressive distributed lag model (ARDL) to evaluate which explanatory variables have the biggest impact on house price growth. As the last exercise, we develop a suite of models that are used to forecast future development of the house price index. The analysis presented in this paper may be viewed as a further step towards more formalised modelling and forecasting of the Lithuanian house price index.

JEL Codes: C22, C32, C53, E37, R30.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

From the bookkeeping perspective, the flipside of bank loan issuance is a simultaneous creation of a deposit in the borrower’s account. By the act of lending banks do not simply intermediate pre-accumulated real resources but rather create new financial resources (money in the form of deposits) and new purchasing power. Being a major driver behind money growth, bank credit directly fuels domestic demand and inflationary pressures and thus needs to be modelled as a monetary phenomenon rather than as a mere reallocation of real resources. To this end, we develop a simple DSGE model and show that the basic DSGE framework, representing an open flexible-price economy with savers and borrowers and a simple bank with an explicit balance sheet, can indeed capture the essence of a bank as a monetary institution. The theoretical model confirms that the financial system is highly elastic in a sense that banks can extend loans at will largely irrespective of pre-accumulated resources and without needing to raise nominal deposit rates or increase financing from abroad. Moreover, in our model, changes in bank credit do have an immediate impact on nominal incomes, domestic demand and real economic activity. Model results are highly relevant from the policy perspective because they explain the fundamental relationship between financial (credit) cycle and the business cycle (e.g. observed income growth can be a consequence of a credit boom) and also suggest that sound domestic banks can stimulate domestic demand and can effectively reduce the developing economy’s reliance on foreign financing. Notably, the model focuses on a small open economy – a member of a monetary union – which thus has no independent monetary policy. We calibrate the model to the Lithuanian data and perform a number of policy-relevant shock experiments.

JEL Codes: E30, E44, E51, G21.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania. 

By resorting to the analytical integrated accounts framework, this paper investigates the relationship between economic and financial imbalances during the recent economic and financial cycle in Lithuania. There is clear evidence from the financial accounts data that there was a pronounced expansion of balance sheets of institutional sectors during the phase of the economic upturn, whereas the economic downturn was essentially a balance-sheet recession characterised by contracting private sector balance sheets and the reversal in credit flows and monetary dynamics. The boom-and-bust cycle was strongly associated with exuberant bank lending during the boom years, followed by a sudden reversal of lending conditions and the subsequent repatriation of debt financing by foreign banks.
The Lithuanian experience also confirms that strong credit and asset price boom accompanied by economic imbalances, and debt financing of current account deficits in particular, is a potentially risky mix of economic conditions. The policy response to crisis was a market-imposed austerity but nevertheless there was a sharp rise in public debt, essentially offsetting deleveraging in the private sector. The effective replacement of growth of private sector debt with a rapid accumulation of public debt was a very important stabilising factor.
Certain characteristics of bank credit (namely, its partial self-financing) imply that under some conditions economic stabilisation could have been achieved through domestic financing. However, the government had to resort to foreign financing, which was rather costly. During the crisis the monetary dynamics was driven by government borrowing from abroad, stepped up capital transfers from abroad and positive current account adjustments, all of which allowed foreign parent banks to withdraw debt financing and replace it with domestic deposit financing.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper we apply the analytical integrated accounts framework to conduct a conceptual analysis of essential macrofinancial linkages. In particular, we analyse the macroeconomic mechanism of the creation of purchasing power through bank credit, explore the partial self-financing property of bank credit and the links between bank credit and money creation, and discuss the role of debt accumulation as a powerful demand-side driver of growth. We argue that creation of money and purchasing power is an indispensable corollary of bank credit issuance. Contrary to conventional wisdom, credit is not predicated on existing savings. It directly adds to domestic demand, which translates into some combination of stronger domestic economic activity, stronger foreign economic activity or higher prices, with particular configuration depending on the structural features of the economy. However, credit-driven growth may result in a systemic over-reliance on continuous debt accumulation and poses the risk of deep structural imbalances and balance sheet recessions.

JEL Codes: E51, E58, G21.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper we analyse determinants of the recent boom-and-bust cycle of the Lithuanian economy with the help of a medium-sized macroeconometric model that incorporates a functional financial block. Special emphasis is put on the role of credit market conditions during the overheating episode. We quantitatively estimate the impact of credit conditions and externally funded bank lending on macroeconomic developments. There is evidence that easy credit conditions and active credit expansion contributed moderately to real economic growth but significantly added to overheating pressures by pushing up real estate prices, encouraging concentration of labour and capital into procyclical sectors and increasing private sector’s debt burden. During the boom episode buoyant external environment provided strong background for export-led growth, which was later strongly affected by temporary foreign trade collapse at the outset of the economic crisis. Model results also suggest that government’s discretionary fiscal policies may have contributed to economic overheating and severity of the ensuing crisis by not adopting sufficiently prudent fiscal stance during the boom episode. The model confirms that more favourable interest rate environment and accommodating fiscal policies are important for providing a temporary relief for the crisis-stricken economy but deep structural transformation of the economy is needed for the sustainable recovery to take hold.

JEL Codes: E10, E17, E37, E51.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper we propose an artificial stock market model based on interaction of heterogeneous agents whose forward-looking behaviour is driven by the reinforcement learning algorithm combined with some evolutionary selection mechanism. We use the model for the analysis of market self-regulation abilities, market efficiency and determinants of emergent properties of the financial market. Distinctive and novel features of the model include strong emphasis on the economic content of individual decision making, application of the Q-learning algorithm for driving individual behaviour, and rich market setup.

JEL Codes: G10, G11, G14.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper we provide a brief introduction to the literature on agent-based financial modelling and, more specifically, artificial stock market modelling. In the selective literature review two broad categories of artificial stock market models are discussed: models based on hard-wired rules and models with learning and systemic adaptation. The paper discusses pros and cons of agent-based financial modelling as opposed to the standard representative-agent approach. We advocate the need for the proper account of market complexity, agent heterogeneity, bounded rationality and adaptive (though not simplistic) expectations in financial modelling. We also argue that intelligent adaptation in highly uncertain environment is key to understanding actual financial market behaviour and we resort to a specific area of artificial intelligence theory, namely reinforcement learning, as one plausible and economically appealing algorithm of adaptation and learning.

JEL Codes: G10, G11, G14, Y20.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.