A Generalised Model of Investment under Uncertainty: Aggregation and Estimation

We propose a structural model of investment which is based on the aggregation of (S,s) investment projects within firms. This encompasses the findings that whilst firm level investment is smooth, plant level investment is lumpy and frequently zero. We undertake stochastic aggregation and derive a structural firm level investment estimator. The empirical performance and fit of this estimator on a panel of manufacturing firms is encouraging and provides an avenue for general policy simulation. This model also explains the rich non-linear dynamics of firm level investment data and the frequent simultaneity of firm level investment and disinvestment. This approach provides an alternative structural estimator to the standard convex adjustment cost models, such as Tobin's Q and the Euler equation. The is important because these estimators, which assume quadratic adjustment costs, appear to be misspecified and subject to a fallacy of composition between smooth firm level investment and lumpy plant level investment. For completeness we also consider time aggregation as an alternative source of smoothing but statistically reject this as being insufficient to smooth investment alone. This test also rejects most plant level data, such as the US\ LRD and UK\ ARD, as being generated from a single (S,s) process.

The Impact of Uncertainty Shocks

Uncertainty appears to jump up after major shocks like the Cuban Missile crisis, the assassination of JFK, the OPEC I oil-price shock and the 9/11 terrorist attack. This paper offers a structural framework to analyze the impact of these uncertainty shocks. I build a model with a time varying second moment, which is numerically solved and estimated using firm level data. The parameterized model is then used to simulate a macro uncertainty shock, which produces a rapid drop and rebound in aggregate output and employment. This occurs because higher uncertainty causes firms to temporarily pause their investment and hiring. Productivity growth also falls because this pause in activity freezes reallocation across units. In the medium term the increased volatility from the shock induces an overshoot in output, employment and productivity. Thus, second moment shocks generate short sharp recessions and recoveries. This simulated impact of an uncertainty shock is compared to VAR estimations on actual data, showing a good match in both magnitude and timing. The paper also jointly estimates labor and capital convex and non-convex adjustment costs. Ignoring capital adjustment costs is shown to lead to substantial bias while ignoring labor adjustment costs does not.

The dynamic effects of real options and irreversibility on investment and labour demand

This paper shows that, contrary to common beliefs, the real options effect of uncertainty plays no role in the long run rate of investment. This is proven for both the standard investment model with Cobb-Douglas production and Brownian motion demand, and also for a broader class of models with multiple lines of capital, labor and general demand stochastics. Real options and irreversibility, however, are shown to play an important role in the short run dynamics of investment and labor demand. Specifically, they reduce the short run response of investment and hiring to current demand shocks, and lead to a lagged response to past demand shocks.

Uncertainty and the Dynamics of R&D

Uncertainty varies strongly over time, rising by 50% to 100% in recessions and by up to 200% after major economic and political shocks. This paper shows that higher uncertainty reduces the responsiveness of R&D to changes in business conditions - a "caution-effect" - making it more persistent over time. Thus, uncertainty will play a critical role in shaping the dynamics of R&D through the business cycle, and its response to technology policy. I also show that if firms are increasing their level of R&D then the effect of uncertainty will be negative, while if firms are reducing R&D then the effect of uncertainty will be positive.

Does Management Matter? Evidence From India

A long-standing question in social science is to what extent differences in management cause differences in firm performance. To investigate this we ran a management field experiment on large Indian textile firms. We provided free consulting on modern management practices to a randomly chosen set of treatment plants and compared their performance to the control plants. We find that adopting these management practices had three main effects. First, it raised average productivity by 11% through improved quality and efficiency and reduced inventory. Second, it increased decentralization of decision making, as better information flow enabled owners to delegate more decisions to middle managers. Third, it increased the use of computers, necessitated by the data collection and analysis involved in modern management. Since these practices were profitable this raises the question of why firms had not adopted these before. Our results suggest that informational barriers were a primary factor in explaining this lack of adoption. Modern management is a technology that diffuses slowly between firms, with many Indian firms initially unaware of its existence or impact. Since competition was limited by constraints on firm entry and growth, badly managed firms were not rapidly driven from the market.management, organization, IT, productivity and India

Patents, productivity and market value: evidence from a panel of UK firms

Patents citations are a potentially powerful indicator of technological innovation. In this paper we describe the IFS-Leverhulme patents dataset that we have constructed by combining information from the US Case-Western Patent database with UK company accounts and share price information from the London Stock Exchange. Patents citations like patentc ounts, arehighly skewed and have a modal lag of four years. Analysing data on over 200 major British firms since 1968, we show that patents have an economically and statistically significant impacton firm-level productivity and market value. Patent citations contain more information than simple counts. A doubling in the stock of citation-weighted patents is associated with a four percent increase in (total factor) productivity and an eight percent increase in market value. As expected patenting and citation information feeds into market values immediately but appears to have some additional lagged effects of productivity suggesting gradual takeup of new technologies.Patents, productivity, market value

Human Resource Management and Productivity

In this chapter we examine the relationship between Human Resource Management (HRM) and productivity. HRM includes incentive pay (individual and group) as well as many nonpay aspects of the employment relationship such as matching (hiring and firing) and work organization (e.g. teams, autonomy). We place HRM more generally within the literature on management practices and productivity. We start with some facts on levels and trends of both HRM and productivity and the main economic theories of HRM. We look at some of the determinants of HRM - risk, competition, ownership and regulation. The largest section analyses the impact of HRM on productivity emphasizing issues of methodology, data and results (from micro-econometric studies). We conclude briefly with suggestions of avenues for future frontier work.human resource management, productivity, personnel economics

Firms with more structured management practices are more productive, innovative and have faster employment growth

In 2010, the US Census Bureau conducted the first large-scale survey of management practices in America, gathering data on more than 30,000 manufacturing plants. Nicholas Bloom and colleagues find strong links between establishments’ performance and the quality of their systems of monitoring, targets and incentives

What is Brexit-related uncertainty doing to UK growth?

The UK will soon vote on whether to end its 43-year membership in the European Union. Opinion polls suggest the vote is too close to call, with the “stay” and “leave” side switching leads on a regular basis, and this uncertainty is reflected in swings in the stock market, explains Nicholas Bloom. Using data from the Economic Policy Uncertainty Index, he explains why the uncertainty could be having a material negative impact on the UK’s economic performance