Lumpy Investment Research Articles

Idiosyncratic Shocks, Lumpy Investment and the Monetary Transmission Mechanism

Abstract Standard (S, s) models of lumpy investment allow us to match many aspects of the micro data, but it is well known that the implied interest rate sensitivity of investment is unrealistically large. In fact, the micro-level lumpiness in investment puts empirical discipline on the modeling of investment decisions, and this makes it hard to explain the monetary policy transmission mechanism.

What Happens to Workers at Firms that Automate?

Abstract We estimate the impact of firm-level automation on individual worker outcomes by combining Dutch micro-data with a direct measure of automation expenditures covering all private non-financial sector firms. Using a novel difference-in-differences event-study design leveraging lumpy investment, we find that automation increases the probability of incumbent workers separating from their employers. Workers experience a 5-year cumulative wage income loss of 9 percent of one year's earnings, driven by decreases in days worked. These adverse impacts of automation are larger in smaller firms, and for older and middle-educated workers. By contrast, no such losses are found for firms' investments in computers.

Lumpy investment and credit risk

We examine the effect of investment lumpiness on firms' default risk. A structural model is established and shows that firms with lumpier (or more indivisible) investments will encounter higher credit risk, all else being equal. We use the model solutions to simulate investment and default dynamics for a variety of firms structurally similar to their empirical counterparts. Using the relative size of investments, time between investments, and the skewness of investment rates as the proxies of investment lumpiness, the regression exercises of the simulated samples demonstrate that the degree of lumpiness is monotonically related to the probability of default. The models' implications are generally supported by reduced-form tests using actual data. This article sheds new light on the linkage between firms' investment patterns and default risk.

Tax Policy and Lumpy Investment Behaviour: Evidence from China’s VAT Reform

AbstractWe incorporate the lumpy nature of firm-level investment into the study of how tax policy affects investment behaviour. We show that tax policies can directly impact the lumpiness of investment. Extensive-margin responses to tax policy are key to understanding the effects of different tax reforms and to designing effective stimulus policies. We illustrate these results by studying China’s 2009 VAT reform, which lowered the tax cost of investment and reduced partial irreversibility—the price gap between new and used capital. Using comprehensive tax survey data and a difference-in-differences design, we estimate a 36$\%$ relative investment increase that is driven by investment spikes. Using a dynamic investment model that fits the reduced-form effects of the reform, we show that policies that directly reduce the likelihood of firm inaction are more effective at stimulating investment.

A Note on nonconvex adjustment costs in lumpy investment models: Mean versus variance

AbstractThis paper revisits the canonical assumption of nonconvex capital adjustment costs in lumpy investment models as in Khan and Thomas [(2008) Econometrica 76(2), 395–436], which are assumed to follow a uniform distribution from zero to an upper bound, without distinguishing between the mean and the variance of the distribution. Unlike the usual claim that the upper bound stands for the size (represented by the mean) of a nonconvex cost, I show that in order to generate an empirically consistent interest elasticity of aggregate investment, both a sizable mean and a sizable variance are necessary. The mean governs the importance of the extensive margin in aggregate investment dynamics, while the variance governs how sensitive the extensive margin is to changes in the real interest rate. As a result, both the mean and the variance are quantitatively important for aggregate investment dynamics.

Lumpy Investment and Credit Risk

Lumpy Investment and Credit Risk

Lumpy Investment, Business Cycles, and Stimulus Policy

I study the aggregate implications of micro-level lumpy investment in a model consistent with the empirical dynamics of the real interest rate. The elasticity of aggregate investment with respect to shocks is procyclical because more firms are likely to make an extensive margin investment in expansions than in recessions. Matching the dynamics of the real interest rate is key to generating this result because it disciplines the interest-elasticity of investment and avoids counterfactual behavior of the model that would otherwise eliminate most of the procyclical responsiveness. Therefore, data on interest rates place important discipline in aggregating micro-level investment behavior. (JEL D25, E13, E22, E23, E43, G31, H25)

Nonconvex Adjustment Cost in Lumpy Investment Models: Mean versus Variance

This paper revisits the canonical assumption of nonconvex capital adjustment costs in lumpy investment models as in Khan and Thomas (2008), which are assumed to follow a uniform distribution from zero to an upper bound, without distinguishing between the mean and the variance of the distribution. Unlike the usual claim that the upper bound stands for the size (represented by the mean) of a nonconvex cost, I show that in order to generate an empirically consistent interest elasticity of aggregate investment, both a sizable mean and a sizable variance are necessary. The mean governs the importance of the extensive margin in aggregate investment dynamics, while the variance governs how sensitive the extensive margin is to changes in the real interest rate. As a result, both the mean and the variance are quantitatively important for aggregate investment dynamics.

HOMEOWNERSHIP AND HOUSING TRANSITIONS: EXPLAINING THE DEMOGRAPHIC COMPOSITION

AbstractWe document the evolution of homeownership rate across various age groups for the period 1995–2015. We find that variations in the homeownership rates are relatively large for the young, which is mostly driven by renter‐to‐owner transitions. In order to explain these empirical facts, we consider a life‐cycle model featuring housing tenure decisions. Housing is modeled as an indivisible and lumpy investment subject to both loan‐to‐value (LTV) and debt‐to‐income (DTI) credit constraints and transaction fees. Our analysis suggests that variations in the DTI limit play a crucial role in accounting for the uneven behavior across age groups.

Lumpy Investment in Dynamic General Equilibrium

Microeconomic lumpiness matters for macroeconomics. According to our DSGE model, it explains roughly 60% of the smoothing in the investment response to aggregate shocks. The remaining 40% is explained by general equilibrium forces. The central role played by micro frictions for aggregate dynamics results in important history dependence in business cycles. In particular, booms feed into themselves. The longer an expansion, the larger the response of investment to an additional positive shock. Conversely, a slowdown after a boom can lead to a long lasting investment slump, which is unresponsive to policy stimuli. Such dynamics are consistent with US investment patterns over the last decade. More broadly, over the 1960-2000 sample, the initial response of investment to a productivity shock with responses in the top quartile is 60% higher than the average response in the bottom quartile. Furthermore, the reduction in the relative importance of general equilibrium forces for aggregate investment dynamics also facilitates matching conventional RBC moments for consumption and employment.

Lumpy investment and expected stock returns

This study investigates the predictability of stock market returns using a novel corporate investment measure that captures the lumpiness of firm-level investment. We find that the proportion of firms with investment spikes (spike) is a strong predictor of excess stock returns. Specifically, an increase in spike significantly lowers future excess stock returns. The predictive ability of spike is consistently observed in both in-sample and out-of-sample tests. Furthermore, spike shows strong predictive ability at the business cycle frequency, suggesting that its predictive ability is driven by the time-varying risk premium associated with business cycles rather than temporary mispricing.

Lumpy Investment, Uncertainty, and Monetary Policy

I argue that monetary policy is less effective at stimulating investment during periods of elevated volatility in firm-level productivity. Empirically, I document that high volatility weakens investment responses to monetary stimulus. I then develop a heterogeneous firm New Keynesian model with lumpy investment to interpret these findings. In the model, non-convex capital adjustment costs create a sizable extensive margin of investment which is more sensitive to changes in both the interest rate and volatility than the intensive margin. When volatility is high, firms tend to stay inactive at the extensive margin, so monetary stimulus motivates less investment at the extensive margin. I find that the quantitative implications of the model are primarily shaped by the specifications of the capital adjustment costs. Unlike much of the prior literature, I use the dynamic moments of investment to identify this key model element. Based on this parameterization, high volatility reduces the effectiveness of monetary stimulus for investment by 30%. This reduction is about half of what I find in the data. Therefore, the effect of monetary policy depends on both the lumpy nature of firm-level investment and fluctuations in volatility.

Firm Heterogeneity in Production-Based Asset Pricing: The Role of Habit Sensitivity and Lumpy Investment

I study the interaction between lumpy investment and asset prices in both time-series and cross-section. To this end, I work with a variant of habit sensitivity function introduced in Campbell & Cochrane (1999). The model produces 100% equity volatility of data by generating volatile marginal utility under the assumption of non-convex adjustment costs. Second, the model reproduces nearly 100% equity premiums of data because it assigns large weights on precautionary savings and constrained firms, respectively. Furthermore, the model can rationalise considerable size premiums as small firms absorb more productivity risks. Finally, the model matches key macroeconomic moments and the cross-sectional investment rate.

Lumpy Investment and Expected Stock Returns

Lumpy Investment and Expected Stock Returns

Homeownership and Housing Transitions: Explaining the Demographic Composition

The homeownership rate was relatively stable for the few decades preceding 1995, followed by a large increase between 1995-2005 and a subsequent decline over the next ten years. We document the evolution of homeownership rate across various age groups for the period 1995-2015. Two interesting empirical findings emerge. First, there are uneven variations in the homeownership rates across age: it is large for the young but small for the old. Second, the total variation is mostly driven by renter-to-owner transitions of the young. We next consider a life-cycle model featuring housing tenure decisions to explain these empirical facts. Housing is modeled as an indivisible and lumpy investment subject to both loan-to-value (LTV) and debt-to-income (DTI) constraints and transaction fees. Our quantitative model reasonably replicates the key distributions and transitions between housing tenures over the life cycle. Our analysis suggests that a variation in the DTI limit plays a crucial role in accounting for the overall rise in homeownership and the uneven behavior across age groups.

Sequential investment in renewable energy technologies under policy uncertainty

Although innovation and support schemes are among the main forces that drive investment in renewable energy (RE) technologies, both involve considerable uncertainty. We develop a real options framework to analyse the impact of technological, policy and electricity price uncertainty on the decision to invest sequentially in successively improved versions of a RE technology. Technological uncertainty is reflected in the random arrival of innovations, and policy uncertainty in the likely provision or retraction of a subsidy that takes the form of a fixed premium on top of the electricity price. We show that greater likelihood of subsidy retraction (provision) lowers (raises) the incentive to invest, and, by comparing a stepwise to a lumpy investment strategy, we show how an embedded option to adopt an improved technology version mitigates the impact of subsidy retraction on investment timing. Specifically, we show how stepwise investment facilitates earlier technology adoption compared to lumpy investment, and that, under stepwise investment, technological uncertainty accelerates technology adoption, thus further offsetting the incentive to delay investment in the light of subsidy retraction.

Real Anomalies

ABSTRACTWe examine the importance of cross‐sectional asset pricing anomalies (alphas) for the real economy. To this end, we develop a novel quantitative model of the cross‐section of firms that features lumpy investment and informational inefficiencies, while yielding distributions in closed form. Our findings indicate that anomalies can cause material real inefficiencies, which raises the possibility that agents who help eliminate them add significant value to the economy. The model shows that the magnitude of alphas alone is a poor indicator of real outcomes, and highlights the importance of the alpha persistence, the amount of mispriced capital, and the Tobin's q of firms affected.

Aggregate Dynamics in Lumpy Economies

In economies with lumpy microeconomic adjustment, we establish structural relationships between the dynamics of the cross-sectional distribution of agents and its steady-state counterpart and discipline these relationships using microdata. Applying our methodology to firm lumpy investment, we discover that the dynamics of aggregate capital are structurally linked to two cross-sectional moments of the capital-to-productivity ratio: its dispersion and its covariance with the time elapsed since the last adjustment. We compute these sufficient statistics using plant–level data on the size and frequency of investments. We find that, in order to explain investment dynamics, the benchmark model with fixed adjustment costs must also feature a precise combination of irreversibility and random opportunities of free adjustment.

Agency costs and the monetary transmission mechanism

Abstract Once New Keynesian (NK) theory is combined with a standard model of lumpy investment, the resulting framework loses its ability to generate a realistic monetary transmission mechanism. This is the puzzle uncovered in Reiter, Sveen, and Weinke [Reiter, M., T. Sveen, and L. Weinke. 2013. “Lumpy Investment and the Monetary Transmission Mechanism.” Journal of Monetary Economics 60: 821–834.]. The simple economic reason behind it is the unrealistically large interest rate elasticity of investment, as implied by the standard theory of lumpy investment. In order to address this puzzle we develop a NK model featuring fully flexible investment combined with a financial friction. This model is used to isolate the quantitative importance of the financial friction for the monetary transmission mechanism.

Optimal proportion decision-making for two stages investment

In two-stage investment decision-making, an enterprise focuses not only on the choice of optimal investment timing, but also on the investment proportion of each stage. By considering the typical two-stage investment decision-making, we analyze the effect of output quantity on price and profit of each stage and construct the model under uncertainty, including the optimal investment timing and proportion. In some situations the investment project is set up with a certain maximum capacity, and this fixed project capacity becomes an upper boundary of its later output that cannot be adjusted in the future. Compared to lumpy investment, this study presents that two-stage investment decision-making allows the enterprise to enter the first stage earlier and the second stage later when choosing the proper investment proportion, which may enhance the investment value. Under increasing uncertainty, the enterprise will enter the first-stage investment later with a larger proportion, and the effect from the change in investment proportion on investment value will decrease.