Chairperson Effects in Monetary Policy Shock Identification

This paper studies the effect of wage rigidities on the transmission of fiscal and monetary policy shocks. We calculate downward wage rigidities across U.S. states using the Current Population Survey. These estimates are used to explain differences in the state-level economic effects of identical national shocks in interest rates and taxes. In line with the role of sticky wages in New Keynesian models, we find that contractionary monetary policy and tax shocks increase unemployment and decrease economic activity in rigid states considerably more than in flexible states. We also find larger and more persistent effects of monetary and tax policy shocks for states where the ratio between minimum and median wage is higher and for states that do not have right-to-work legislation.

PurposeThis paper aims to investigate whether negative and positive monetary policy (MP) shocks have asymmetric impacts on corporate firms’ investment decisions in Pakistan using firm-level panel data set. Moreover, the authors emphasized on symmetric effects of MP; the authors examine whether high-leverage and low-leverage firms respond differently to negative and positive unanticipated shocks in MP instruments.Design/methodology/approachIn contrast to the conventional framework of VAR, it uses an alternative methodology of Taylor rule to estimate unanticipated MP shocks. The two-step system-generalized method of movement (GMM) estimation method is applied to examine the effect of MP shocks on firm investment through leverage-based asymmetry.FindingsThe two-step system-GMM estimation results indicate that unanticipated negative changes (unfavorable shocks) in MP instruments have negative, significant effects on investment. In contrast, unanticipated positive changes (favorable shocks) have statistically insignificant impacts on firm investment. The results also reveal that firm leverage has a significant role in establishing the effect of unanticipated negative changes in MP instruments on investments. Finally, the results indicate that high-leverage firms respond more to negative changes than low-leverage firms. Yet, the results show that only low-leverage firms positively respond to unanticipated positive shocks in MP.Practical implicationsThe findings of the paper suggest that MP authorities should pay due attention to the asymmetric effects of MP shocks on firm investment while designing MP. Because firm leverage has a significant influence on the effects of MP shocks, firm managers should take into account such role of leverage while deciding capital structure of their firms.Originality/valueFirst, unlike “Keynesian asymmetry” and most of published empirical research work, the authors use both unanticipated negative and positive MP shocks simultaneously. Departing from the conventional empirical literature, the authors differentiate between unanticipated positive and negative shocks in MP using the backward-looking Taylor rule. Second, the authors contribute to the existing literature by investigating the differential effects of positive and negative unanticipated MP shocks on firms’ investment decisions. Unlike the published studies that have emphasized on the symmetric effects of MP, the authors examine whether high-leverage and low-leverage firms respond differently to negative and positive unanticipated shocks in MP instruments.

Comment

This paper aims to contribute to the empirical literature on the interaction between monetary and fiscal policy. We consider the impact of monetary and fiscal policy shocks on inflation and output dynamics using a Time-Varying Parameter Factor-Augmented VAR (TVP-FAVAR). In baseline results from a linear model, including fiscal policy in the factors has implications for the impact of monetary policy shocks on inflation. This can be explained with the generated positive wealth effects. Moreover, results from our TVPFAVAR indicate that price puzzles from monetary policy shocks are more accentuated during particular regimes. For example, under coordination of Fiscal-Active with Monetary-Passive policy during the Burns and Volcker regime of 1970s and 1980s inflation rise in response to a contractionary monetary policy shock. Likewise the baseline model, the underlying mechanism can be explained through the wealth effect channel. Finally, the results of a fiscal expansionary policy provide support for the non-Ricardian view on fiscal policy within both the linear and non-linear FAVAR model.

Are global spillovers complementary or competitive? Need for international policy coordination

Abstract: This study investigates the effects of monetary and fiscal policies on the real output growth in a small open economy. It is a country‐specific, time series study that verifies the implication of increasing economic openness on the efficacy of monetary and fiscal policy. A modified GARCH model was used to estimate the anticipated and unanticipated shocks. Two measures of fiscal and monetary shocks were combined with openness and real oil price shocks in a VECM model to assess the effects of anticipated and unanticipated policy shocks on the output equations. The empirical results showed that anticipated and unanticipated fiscal and monetary shocks had no significant positive effects on real output. This suggests that the open macroeconomic version of the policy ineffectiveness proposition was valid for both monetary and fiscal policy shocks in Nigeria. This is in consonance with earlier works in this area. Furthermore, the degree of openness and oil price shocks had a negative implication on the efficacy of macroeconomic policy in Nigeria; also in agreement with the Dutch Disease Syndrome. Finally, the policy implication of this study therefore is that trade liberalization policy should be implemented cautiously. The Nigerian economy is weak to withstand the unwholesome consequences of full economic integration.

Managing price and financial stability objectives in inflation targeting economies in Asia and the Pacific

This paper develops a New Keynesian model with on-the-job search. Workers are allowed to search on the job in order t o find a better job. I analyze how output, consumption, inflation, unemployment, and t he other labor market variables respond to productivity and monetary policy shocks. I allow the labor input to change both at the extensive margin and at the inte nsive margin. This generates a lower elasticity of marginal cost with respect to o utput which is important in obtaining the sluggish response of inflation. I fin d that output and consumption show large and persistent responses to productivity and monetary policy shocks, whereas labor market variables do not show persiste nt effects and adjust very quickly in response to monetary policy shocks. On-t he-job search mechanism also eliminates the need for exogenous wage rigidity and reduces the average duration of price contracts, which is consistent with the micro data. The increasing search activity by the employed creates an incentive for t he firms to post vacancies and helps in achieving the relatively smooth behavior o f wages over the cycle without assuming any exogenous and ad-hoc wage rigidity.

The purpose of this study is to identify the effects of monetary policy and macroeconomic shocks on the dynamics of the Brazilian term structure of interest rates. We estimate a near-VAR model under the identification scheme proposed by Christiano et al. (1996, 1999). The results resemble those of the US economy: monetary policy shocks that flatten the term structure of interest rates. We find that monetary policy shocks in Brazil explain a significantly larger share of the dynamics of the term structure than in the USA. Finally, we analyse the importance of standard macroeconomic variables (e.g. GDP, inflation and measure of country risk) to the dynamics of the term structure in Brazil.

This paper analyzes the importance of monetary and fiscal policy shocks in explaining U.S. macroeconomic fluctuations, and establishes new stylized facts. The novelty of our empirical analysis is that we jointly consider both monetary and fiscal policy, whereas the existing literature only focuses on either one or the other. Our main findings are twofold: fiscal shocks are relatively more important in explaining medium cycle fluctuations whereas monetary policy shocks are relatively more important in explaining business cycle fluctuations, and failing to recognize that both monetary and fiscal policy simultaneously affect macroeconomic variables might incorrectly attribute the fluctuations to the wrong source.

This paper analyzes the importance of monetary and fiscal policy shocks in explaining US macroeconomic fluctuations, and establishes new stylized facts. The novelty of our empirical analysis is that we jointly consider both monetary and fiscal policy, whereas the existing literature only focuses on either one or the other. Our main findings are twofold: fiscal shocks are relatively more important in explaining medium cycle fluctuations whereas monetary policy shocks are relatively more important in explaining business cycle fluctuations; and failing to recognize that both monetary and fiscal policy simultaneously affect macroeconomic variables might incorrectly attribute the fluctuations to the wrong source.

This study concerns two potential channels for the transmission of monetary policy to the farm sector in the United States. The first one is the money channel where I use a relative-price model to explain the effect of monetary policy shocks on relative farm prices. The second one is the credit channel where I use the Flow of Funds Accounts (FOFA) data to assess the effect of monetary policy shocks on net funds raised in the farm sector;The equilibrium relative-price model provides a linkage between monetary policy shocks and relative farm prices. The model shows that monetary policy can affect relative farm prices if aggregate price information is imperfect and if supply and demand elasticities in the farm and nonfarm sectors are different. The short-run elasticity of supply of farm products is argued to be less than that of nonfarm products because of differences in the production processes. This characteristic of farm production causes relative farm prices to fall initially in response to a contractionary monetary policy shock;The credit channel for the transmission of monetary policy is another way monetary policy can affect the farm sector. The credit view holds that monetary policy affects the borrowing and lending activities of the farm sector primarily because it affects the extent of financial intermediation. It suggests that the amount of bank loans might also be an important indicator of the tightness of monetary policy;A semi-structural vector autoregression (VAR) model is used to develop two VAR based policy shock measures---the federal funds rate and nonborrowed reserves. The effects of monetary policy shocks on the farm sector are then assessed using dynamic response functions obtained through the VAR model;Relative farm prices show a steady and persistent decline after a contractionary monetary policy shock, while net funds raised in the farm sector increase for roughly a year then decline. The initial rise in the net funds raised reflects the difficulty for farmers to quickly alter their nominal expenditures. Eventually, they reduce their nominal expenditures and net funds raised decline as predicted by the credit view.

Yet another approach to identifying structural VAR shocks is to rely on additional data not included among the VAR model variables. This chapter discusses two such approaches. The first approach relies on information from high-frequency futures prices, whereas the second approach relies on external exogenous instruments such as measures of exogenous OPEC oil supply shocks or the narrative measures of exogenous monetary policy shocks and exogenous fiscal policy shocks already discussed in Chapter 7. Identification Based on High-Frequency Futures Prices Discomfort with semistructural VAR models of monetary policy, in which the monetary policy shock is identified based on a recursive ordering of the model variables, has stimulated the development of yet another approach to identification that relies on high-frequency futures market data to identify monetary policy shocks. One motivation for this approach is that the sequences of policy shocks identified by recursive structural VAR models do not always correspond to common perceptions of when policy shocks occurred and indeed vary widely across models (see Rudebusch 1998). The other motivation is that the reduced-form interest rate forecasts of conventional VAR models of monetary policy are difficult to reconcile with financial market measures of interest rate expectations. For example, Rudebusch (1998) documents a low correlation between the quarterly reduced-form prediction errors for the federal funds rate implied by conventional VAR models of monetary policy and the quarterly changes in the expected federal funds rate implied by the prices of federal funds futures contracts, defined as where quarter t contains months, and is the actual federal funds rate in month i , and denotes the j -months ahead expected federal funds rate at the end of month i , as measured by the price of the federal funds futures contract. The financial market shocks statistically explain only between 10% and 25% of the variation in the quarterly VAR prediction errors, based on data since 1988 when federal funds futures contracts were introduced. Rudebusch interprets this evidence as suggesting that the reduced-form representation of VAR models of monetary policy is inherently misspecified, perhaps reflecting an informational deficiency of these models (see also Chapter 16).

PurposeThis paper investigates the impact of a monetary policy shock on the production of a sample of 312 industries in manufacturing, mining and utilities in the United States using a factor-augmented vector autoregression (FAVAR) model.Design/methodology/approachThe authors use a FAVAR model that builds on Bernanke et al. (2005) and Boivin et al. (2009). The main assumption in this model is that the dynamics of a large set of macro variables are captured by some observed and unobserved common factors. The unobserved factors are extracted from a large set of macroeconomic data. The key advantage of using this model is that it allows extracting the impulse responses of a wide range of macroeconomic variables to structural shocks in the federal funds rate.FindingsThe results indicate that industries exhibit differential responses to an unanticipated monetary policy tightening. In general, manufacturing industries appear to be more sensitive compared to mining, and utility industries and durable manufacturing industries are found to be more sensitive than those within nondurable and other manufacturing industries to a monetary policy shock. While all industries respond to the policy shock, most of the responses are reversed between 12 and 22 months.Research limitations/implicationsThe implication of our results is that monetary policy can be used to impact most US industries for four years and beyond. The existence of disparate responses across industries underscores the difficulty of implementing a monetary policy that will generate the same impact across industries. As the effects of the policy are distinct, policymakers may want to attend to the unique impacts and implement industry-specific policy.Practical implicationsThe study is important in the context of the current challenges in the US economy caused by the spread of coronavirus. For example, to tackle the current pandemic, the researchers are trying to come up with cures for COVID-19. A considerable response of the chemical industry that provides materials to pharmaceutical and medicine manufacturing to the monetary policy shock implies that an expansionary monetary policy may facilitate an invention and adequate supply of the cure later on. The same policy may not effectively stimulate production in apparel or leather product industries that are being hard hit by the pandemic.Originality/valueThe study contributes to the literature in broadly two aspects. First, to the best of our knowledge, this is the first paper that investigates the impact of a monetary policy shock on a sample of 312 industries in manufacturing, mining and utilities in the US. Second, to identify structural shocks and investigate the effects of monetary policy shocks on economic activity, the authors diverge from the literature's traditional approach, i.e. the vector autoregression (VAR) method and use a FAVAR method. The FAVAR provides a comprehensive description of the impact of a monetary policy innovation on different industries.

We estimate an open economy VAR model to quantify the effect of monetary policy and capital inflows shocks on the US housing market. The shocks are identified with sign restrictions derived from a standard DSGE model. We find that monetary policy shocks have a limited effect on house prices and residential investment. In contrast, capital inflows shocks driven by an increase in foreign savings have a positive and persistent effect on both housing variables. Other sources of capital inflows shocks, such as foreign monetary expansion or an increase in aggregate demand in the US, have a more limited role.