Publications

Using two different methodologies, we estimate time-varying natural real rates of interest for a majority of euro area (EA) countries, including Lithuania. We find that natural real rates have been declining, particularly since 2008, albeit to different extent across EA countries. Lower rates could (at least partly) be explained by lower productivity and population growth. In line with previous literature, we find evidence of a substantial dispersion of the natural interest rate across EA economies. This became especially evident during the financial crisis of 2008-2009 and the sovereign debt crisis of 2010-2012, while estimates of natural rates tend to converge during "calm" periods. Estimates of natural rates for Lithuania were significantly above the estimates of core EA countries over 2002-2008, but this has changed after the crisis. From 2011 the estimates of natural rates for Lithuania tend to be close to the average for EA countries.

JEL Codes: C32, E32, E43, E52.

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

The article analyzes recent developments in investments in Lithuania using a broad set of possible drivers, including EU funds. We apply a Bayesian VAR setup with data from 1997Q1 to 2019Q4. We also examine and compare business vs. government investments and different types of investments, especially innovative investments. We find that total investments are basically driven by the data on business investments. The main outcomes are mostly in line with the literature, but we do see some crucial differences across types. Key results include: (1) a small role for lending rates as compared to other factors, largely limited to the global financial crisis; (2) the crucial role of demand-side variables, i.e. foreign demand or private consumption; (3) pro-cyclicality in government investments and a positive correlation with business investments; (4) the importance of uncertainty for some sectors, that positively drives only the more innovative/intangible investments; and (5) despite the fact that EU funds do feed investments, there is a crowding-out in the short run for business-related investments, while there is some positive contribution to public investments.

JEL Codes: E32, D24, D61, C32.

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

The aim of this paper is to assess how relevant is the topic of sovereign bond valuations in official ECB Executive Board member speeches and, in particular, under what circumstances do ECB officials begin communicating the driving factors of sovereign bond pricing. For this purpose, we downloaded over 2000 public ECB Executive Board member speeches and applied various text mining techniques. The visual analysis revealed that the importance of the topic of sovereign bond pricing and related risk factors in ECB officials’ speeches has greatly fluctuated over time. The main structural break points were linked to the financial market turbulences, but this topic, possibly due to the introduction of sovereign bond purchases, remained relatively popular even after stress episodes. The linkages between the publicly communicated terms of sovereign bond pricing and related risk factors were rather complex and change in respect to the market situation. Meanwhile, the sentiment balance of the credit risk factor was usually on the negative side, while the ones of other terms were much more neutral.

JEL Codes: C80, E43, E58, G12.

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

This paper analyzes the transition to a low-carbon economy and its effects on macroeconomic quantities and asset prices. Empirically, we document that the relative valuation of fossil fuel firms has significantly declined with the rise of climate change risk awareness. We develop a macro asset pricing model for the climate transition that matches this empirical fact and allows us to characterize the dynamics of macroeconomic aggregates and asset prices during and after the transition. In particular, we analyze (i) firm valuation dynamics, (ii) climate policy risk premia, (iii) capital reallocation between sectors, and (iv) the behavior of oil prices.

JEL Codes: E2, E3, G12, Q43.

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