How important can bank lending shocks be for economic fluctuations?

Halvorsen, Jørn Inge; Jacobsen, Dag Henning

doi:10.1016/j.najef.2014.05.006

Cited by 16 publications

(14 citation statements)

References 31 publications

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“…Barnett and Thomas (2014) find that loan supply shocks explain most of the weakness in lending in the UK since the onset of the crisis and between a third and a half of the fall in GDP below its historic trend. Halvorsen and Jacobsen (2014) also find that lending shocks explain between 10 and 20 percent of output gap variance in Norway and the UK. Regarding the euro area, Hristov, Hülsewig and Wollmershäuser (2012) find that loan supply shocks have had a strong effect on lending and GDP growth during the financial crisis, with some cross-country heterogeneity regarding the timing and the magnitude of the shocks.…”

Section: Introductionmentioning

confidence: 74%

“…We also include a constant term in the VAR. Although most studies use the GDP deflator as an indicator of price movements, we decided to use consumer price inflation because it is the indicator monetary policy-makers usually focus on when making policy decisions (Halvorsen and Jacobsen, 2014), which is also the case in Macedonia. Further, by using the policy rate, we deviate from most of the literature, which tends to use interbank rates as an indicator of the monetary policy stance.…”

Section: Data and Methodology 21 Datamentioning

confidence: 99%

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Loan Supply Shocks in Macedonia: A Bayesian SVAR Approach with Sign Restrictions

Kabashi

Suleva

2016

CES

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This paper analyzes the effects of loan supply, as well as aggregate demand, aggregate supply and monetary policy shocks between 1998 and 2014 in Macedonia using a structural vector autoregression model with sign restrictions and Bayesian estimation. The main results indicate that loan supply shocks have no significant effect on loan volumes and lending rates, or on economic activity and prices. The effects of monetary policy on lending activity are fairly limited, although there is some evidence that it affects lending rates more than loan volumes. Monetary policy shocks have strong effects on inflation, while the central bank reacts strongly to adverse shocks hitting the economy. Baseline results are confirmed by several robustness checks. According to historical decomposition, the lending activity was supporting economic growth before and during the crisis, but its contribution became negative during the recovery and it was a drag on growth until the end of the period. Pre-crisis GDP growth is mostly explained by supportive monetary policy. However, the restrictive monetary policy during the crisis contributed to the fall of GDP, before becoming supportive again during the early stages of the recovery. Policy rates in recent years mostly reflect subdued lending activity and aggregate supply factors, which the central bank tries to counteract with a more accommodative policy. monetary policy, aggregate demand and aggregate supply shocks. It follows the recent literature on loan supply shocks, particularly regarding the empirical methodology. The main contribution of the paper is that it focuses on an important economic and policy issue in Macedonia, which has not been previously empirically investigated. By using Bayesian SVAR with sign restrictions, the paper avoids some of the drawbacks of classical econometric methods arising from the relatively short data series with structural and methodological breaks, which is common for transition countries. To the best of our knowledge, this is the first paper which tries to apply this technique to economic data on Macedonia.The paper starts with discussing data and methodology in Section 2. Section 3 presents baseline results. Section 4 provides robustness checks. The last section provides a conclusion.

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Section: Introductionmentioning

confidence: 74%

Section: Data and Methodology 21 Datamentioning

confidence: 99%

Loan Supply Shocks in Macedonia: A Bayesian SVAR Approach with Sign Restrictions

Kabashi

Suleva

2016

CES

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“…A fast growing literature has attempted to identify credit supply shocks through vector autoregressions (VAR) by imposing sign restrictions on impulse responses (Halvorsen and Jacobsen, 2009;Busch et al, 2010;De Nicol o and Lucchetta, 2011;Eickmeier and Ng, 2011;Tam asi and Vil agi, 2011;Gambetti and Musso, 2012;Hristov et al, 2012;Barnett and Thomas, 2013;Darracq Paries and De Santis, 2013;Houssa et al, 2013;Darracq Paries et al, 2014;Kick, 2014), or by using other identification schemes Abildgren, 2012;Darracq Paries and De Santis, 2013). 1 A constant 1 There have also been attempts in the theoretical literature to better capture shifts in the supply of credit by expanding the focus beyond borrowing constraints in collateral markets and emphasizing the role of constraints on lenders (Justiniano et al, 2014). parameter approach, as adopted in almost all these studies, might not do full justice to the timevarying nature of macroeconomic relationships that these models try to capture.…”

Section: Introductionmentioning

confidence: 99%

The macroeconomic impact of financial fragmentation in the euro area: Which role for credit supply?

Bijsterbosch

Falagiarda

2015

Journal of International Money and Finance

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“…Table 2 summarizes those studies. Halvorsen and Jacobsen (2009) analyze the importance of a loan supply shock on the real activity in Norway and the United Kingdom. They use six endogenous variables: inflation, GDP gap (de-trended real GDP), the -mix‖ variable, the real effective exchange rate, the real house price, and the domestic short-term interest rate.…”

Section: Literature Reviewsmentioning

confidence: 99%

Bank Lending Channel in Transmission of Monetary Policy in Japan, 2000–2012: The Sign Restrictions VAR Approach

Kumamoto¹,

Zhuo²

2017

AEF

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This paper investigates empirically whether the bank lending channel of monetary policy existed in Japan from 2000 to 2012. We employ the sign restrictions VAR approach to deal with the identification problem. In particular, we focus on the differential effects of a quantitative easing monetary policy regardless of bank (City banks vs. Regional banks) and firm (all enterprises vs. small and medium-sized enterprises-SMEs) size. Our impulse response function analyses show that following a quantitative easing monetary policy shock, the lending of Regional banks increases more than that of City banks, and the bank lending rate of Regional banks declines in a larger magnitude. Moreover, the responses of output to reserve supply are larger in Regional banks than that in City banks. Our variance decomposition analyses show that a larger proportion of the forecast error variance in the bank lending of Regional banks relative to City banks, and a larger proportion of the forecast error variance in the bank lending to SMEs relative to all firms can be explained by monetary policy shock. Similarly, the loans of Regional banks have a larger impact on output than the loans of City banks, and the loans to SMEs have a larger impact on output than the loans to all firms. Moreover, output is more affected by the reserve supply to Regional banks than to City banks. These results together indicate that a quantitative easing policy has a greater impact on the real economy through the lending of Regional banks.

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How important can bank lending shocks be for economic fluctuations?

Cited by 16 publications

References 31 publications

Loan Supply Shocks in Macedonia: A Bayesian SVAR Approach with Sign Restrictions

Loan Supply Shocks in Macedonia: A Bayesian SVAR Approach with Sign Restrictions

The macroeconomic impact of financial fragmentation in the euro area: Which role for credit supply?

Bank Lending Channel in Transmission of Monetary Policy in Japan, 2000–2012: The Sign Restrictions VAR Approach

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