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Abstract
What would have been the hypothetical effect of monetary policy shocks had a country never joined the euro area, in cases where we know that the country in question actually did join the euro area? It is one thing to investigate the impact of joining a monetary union, but quite another to examine two things at once: joining the union and experiencing actual monetary policy shocks. We propose a methodology that combines synthetic control ideas with the impulse response functions to uncover dynamic response paths for treated and untreated units, controlling for common unobserved factors. Focusing on the largest euro area countries, Germany, France, and Italy, we find that an unexpected rise in interest rates depresses inflation and significantly appreciates exchange rate, whereas GDP fluctuations are less successfully controlled when a country belongs to the monetary union than would have been the case under the independent monetary policy. Importantly, Italy turns out to be the overall beneficiary, since all three channels – price, GDP, and exchange rate – deliver the desired results. We also find that stabilizing an economy within a union requires somewhat smaller policy changes than attempting to stabilize it individually, and therefore provides more policy space.
Keywords: Dynamic causal effects; Monetary union; Price puzzle; Common factors.
JEL codes: C14; C32; C33; E52.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Dancing Alone or Together: The Dynamic Effects of Independent and Common Monetary Policies
Does It Matter When Labor Market Reforms Are Implemented? The Role of the Monetary Policy Environment
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Abstract
Do labor market reforms initiated in periods of loose monetary policy yield different outcomes from those that were introduced in periods when monetary tightening prevailed? Since economic theory usually pays attention to the steady state change and ignores business cycle interactions of structural reforms, we connect local projection methodology with the Mallow’s Cp averaging criterion to arrive at an inference that does not require knowledge of the exact functional form, is robust to mis-specification, admits non-linearities, and cross-sectional dependence and addresses uncertainty regarding interactions between labor reforms and macroeconomy. We also develop a test to check the importance of monetary policy for any horizon and the entire impulse response function, taking the multiple testing problem into account. We document that replacement rates deliver substantially different outcomes on real GDP, inflation and real effective exchange rate, whereas labor activation schemes bear different effects on unemployment in low- and high-interest rate environments. There is also evidence of monetary policy trend playing an important role as well as increasing synchronized monetary and labor market policies across European countries.
JEL Codes: C33, C54, E52, E62, J08, J38.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Slicing up inflation: analysis and forecasting of Lithuanian inflation components
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Abstract
In this paper we model five Lithuanian HICP subcomponents in a medium scale Bayesian VAR framework. We deal with the parameter proliferation problem by setting the appropriate amount of shrinkage determined in the out-of-sample forecasting exercise. The main body of the paper consists of displaying the model’s performance in two applications: forecasting and analysis of inflation determinants. We find the model’s forecasts to be competitive against the univariate statistical models, particularly in the cases of predicting processed food and energy goods inflation. What is more, exercises based on conditional forecasting show that these two indices make the best use of accurate conditional information in terms of improving predicting accuracy. In the decomposition of the drivers of HICP components, we demonstrate that both, domestic and foreign factors can be prevalent inflation determinants in certain time periods. We also find some evidence on employees’ bargaining power playing a role in determining the Lithuanian consumer price inflation.
JEL Codes: C32, C53, E37.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Labour market institutions in open economy
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Abstract
This paper builds a theoretical model that introduces frictional unemployment in a two-sector multi-worker heterogeneous firms model with a dynamic matching process. In doing so, we have a rich environment that combines product, labour, and international markets. A change in labour market policies (unemployment benefits and employment contingent subsidies) transforms the share of exporters and affects average productivity. Empirical evidence confirms a robust positive effect of employment subsidies on openness, little, if any, impact of subsidies and a positive effect of replacement rate on unemployment. Closure of equilibrium plays an important role to explain data facts about employment subsidies: using sectoral arbitrage condition, subsidies cease affecting unemployment and make openness grow, consistently with the empirical evidence. Unemployment benefits, on the other hand, make unemployment and openness rise, independently of sectoral reallocations. In addition, we find that unemployment benefits bear different policy implications with regards to international coordination than employment subsidies.
JEL Codes: E24, F12, F16.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Openness and structural labour market reforms: Counterfactuals for Lithuania
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Abstract
This paper deals with the macroeconomic responses to labour market reforms; something of utmost importance in times of monetary policy reaching its limits to affect real economy. We shed more light on the plausible macroeconomic reactions to the ex ante (planned but not implemented yet) reforms in the labour market, taking a currently proposed Social Model in Lithuania as an example. Not only contributing to the current debate on the efficacy of announced structural reforms, we also add to the literature on policy evaluation by assessing reforms from a global perspective. Omission of an international dimension could lead to seriously biased results on policy effects for any open and small economy. Taking trade connectivity and openness into account, we demonstrate macroeconomic reactions to shocks in unemployment benefits, active labour market policies, and tax wedge on the reforming economy. We contrast the results with the approach when global interdependencies are ignored – still a standard practice. Using a satellite model for the intermediate trade, we link the global framework with the sectoral extensive margin, which changes some of the initial findings. A discussion on counterfactuals, which use both cross-sectional and temporal dimensions to tackle anticipation effects, is also presented.
JEL Codes: C33, C54, E62, J38.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Monetary policy transmission: the case of Lithuania
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Abstract
In this paper we study the effect of a (standard) monetary policy shock in the euro area on the Lithuanian economy. For this purpose we employ a structural vector autoregressive (SVAR) model incorporating variables from both, the euro area and Lithuania. We identify the system using short-term zero restrictions. The model exhibits a block exogenous structure to account for the fact that Lithuania is a small economy and Lithuanian macro variables do not have a significant effect on the euro area variables. In general, we find that a monetary policy shock in the euro area has a stronger effect on the Lithuanian economy than it does on the euro area economy, though the effects are not significant, preventing firm conclusions. We further broaden our analysis employing a panel VAR model for the three Baltic states. This allows us to not only explore the time variation of the euro area monetary policy transmission in the Baltics, but also helps to verify our initial results. The effects are stronger when estimated using the panel VAR model.
JEL Codes: C32, C33, E52.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Global perspective on structural labour market reforms in Europe
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Abstract
Appendix (6.9 MB download icon)
Recent turbulent times have once again demonstrated how important flexible product and labour markets are to dampen the effects of adverse economic shocks. A number of labour market reforms have been implemented to enhance economic resilience and flexibility. However, accounting for the efficacy of policy interventions requires going beyond national boundaries and evaluating international interactions and global interdependencies, which may strengthen or weaken economic responses. Concentrating on open European economies, this paper deals with labour market institutions and structural reforms in a general equilibrium framework, which allows to analyse the intricate connections between labour policy choices and international trade (openness), paying special attention to labour market policy shocks. Amid discussions about a fiscal union in Europe, we empirically demonstrate that labour market policies can have positive and negative spillovers to trading partners, thereby calling for coordinated policies within a trading bloc. We answer three types of questions: what would have happened had all economies implemented structural labour market reforms simultaneously? How heterogeneous are responses in a single economy to shocks conducted in every other country? Relatedly, how heterogeneous are responses by all economies to a reform in one given economy?
JEL Codes: C32, C33, E24, F12, F16.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Forecasting Lithuanian economic activity: The role of confidence indicators
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Abstract
The article examines the usefulness of six sector-based confidence indicators in forecasting Lithuanian short-term sectoral economic activity. All six sentiment indicators are examined side-by-side, which allows us to compare their properties, informational content and marginal contribution in forecasting. One of the properties common to all the confidence indices is that the confidence indices’ levels are more related to annual activity changes than to quarterly changes, which motivates us to take into account as well the change in the confidence index level. We find consumer, construction, and economic sentiment indicators to be the most reliable of the six indices, while the manufacturing sentiment index was the least useful in forecasting. We assess the marginal impact of the indicators, employing factor models augmented by additional regressors. Our results also suggest that information on sentiment in one sector is useful in forecasting activity of other sectors as well. The relationship between consumer confidence and private consumption seems to be a somewhat more interesting case than the others, as the level of consumer confidence is statistically significant in regressions when other available economic information is already taken into account. Our interpretation is that the consumer confidence indicator is a proxy of a structural consumption parameter, such as marginal propensity to consume.
JEL Codes: C33, C53.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Forecasting Lithuanian inflation
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Abstract
The paper presents a short-term Lithuanian inflation forecasting model for predicting monthly inflation of 5 main HICP subgroups. We model inflation employing a set of univariate equations, which are mainly based on firms’ mark-up pricing. We make use of disaggregate HICP data, consisting of 92 price series, which naturally evokes discussion of potential pros and cons of forecasting disaggregate series vs. forecasting an aggregate. Besides exploring potential gains of using disaggregate data, we are also interested in the international commodity prices transmission mechanism, which we implement employing a distributed lag model. To examine the performance of model’s forecasts, we employ a recursive pseudo real-time out-of–sample forecasting exercise, generating inflation forecasts up to 15 months ahead. We find that our suggested set of univariate equations produce more accurate forecasts than the competing factor model, VARX model and various benchmark models for all 5 HICP subgroups.
JEL Codes: C52, C53, E37.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
Generating short-term forecasts of the Lithuanian GDP using factor models
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Abstract
This paper focuses on short-term Lithuanian GDP forecasting using a large monthly dataset. The forecasting accuracy of various factor model specifications is assessed using the out-of-sample forecasting exercise. It is argued that factor extraction by using a simple principal components method might lead to a loss of important information related GDP forecasting, therefore, other methods should be also considered. Performance of several factor models, which relate the factor extraction step to GDP forecasting, was tested. The effect of using weighted principal components model, with weights depending on variables’ absolute correlation with GDP, was explored in greater detail. Although factor models performed better than naive benchmark forecast for GDP nowcasting and 1 quarter ahead forecasting, we were unable to set up the ranking among different factor model specifications. We also find that a small scale factor model with 5 variables (which could be regarded as the most important monthly variables for GDP nowcasting) is able to nowcast GDP better than models with a full data set of 52 variables, which might indicate that for the case of the Lithuanian economy, a smaller scale factor models may be more suitable.
JEL Codes: C22, E37.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.