Why is it so Hard to Value Intangibles? Evidence from Investments in High-Technology Start-Ups

The paper uses a range of primary-source empirical evidence to address the question: ‘why is it to hard to value intangible assets?’ The setting is venture capital investment in high technology companies. While the investors are risk specialists and financial experts, the entrepreneurs are more knowledgeable about product innovation. Thus the context lends itself to analysis within a principal-agent framework, in which information asymmetry may give rise to adverse selection, pre-contract, and moral hazard, post-contract. We examine how the investor might attenuate such problems and attach a value to such high-tech investments in what are often merely intangible assets, through expert due diligence, monitoring and control. Qualitative evidence is used to qualify the more clear cut picture provided by a principal-agent approach to a more mixed picture in which the ‘art and science’ of investment appraisal are utilised by both parties alike

The regional electricity generation mix in Scotland: A portfolio selection approach

Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be “inefficient” in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost.

Marriage as a Rat Race: Noisy Pre-Marital Investments with Assortative Matching

We study the incentive to invest to improve marriage prospects, in a frictionless marriage market with non-transferable utility. Stochastic returns to investment eliminate the multiplicity of equilibria in models with deterministic returns, and a unique equilibrium exists under reasonable conditions. Equilibrium investment is efficient when the sexes are symmetric. However, when there is any asymmetry, including an unbalanced sex ratio, investments are generically excessive. For example, if there is an excess of boys, then there is parental over-investment in boys and under-investment in girls, and total investment will be excessive.

Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas

We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

Transaction Costs and Institutions: Investments in Exchange

This paper proposes a simple model for understanding transaction costs for their composition, size and policy implications. We distinguish between investments in institutions that facilitate exchange and the cost of conducting exchange itself. Institutional quality and market size are determined by the decisions of risk averse agents and conditions are discussed under which the efficient allocation may be decentralized. We highlight a number of differences with models where transaction costs are exogenous, including the implications for taxation and measurement issues.

Political Risk, Economic Integration, and the Foreign Direct Investment Decision

In this paper we analyse the impact of policy uncertainty on foreign direct investment strategies. We also consider the impact of economic integration upon FDI decisions. The paper follows the real options approach, which allows investigating the value to a firm of waiting to invest and/or disinvest, when payoffs are stochastic due to political uncertainty and investments are partially reversible. Across the board we find that political uncertainty can be very detrimental to FDI decisions while economic integration leads to an increasing benefit of investing abroad.

The Global Side of the Investment-Savings Puzzle

In this paper we re-examine the long standing and puzzling correlation between national savings and investment in industrial countries. We apply an econometric methodology that allows us to separate idiosyncratic correlation at the country level from correlation at the global level. In a major break with the existing literature, we find no evidence of a long run relationship in the idiosyncratic components of savings and investment. We also find that the global components in savings and investments comove, indicating that they react to shocks of a global nature.

Booms, Recessions and Financial Turmoil: A Fresh Look at Investment Decisions under Cyclical Uncertainty

The paper studies the interaction between cyclical uncertainty and investment in a stochastic real option framework where demand shifts stochastically between three different states, each with different rates of drift and volatility. In our setting the shifts are governed by a three-state Markov switching model with constant transition probabilities. The magnitude of the link between cyclical uncertainty and investment is quantified using simulations of the model. The chief implication of the model is that recessions and financial turmoil are important catalysts for waiting. In other words, our model shows that macroeconomic risk acts as an important deterrent to investments.

The Timing of Asset Trade and Optimal Policy in Dynamic Open Economies

Using a standard open economy DSGE model, it is shown that the timing of asset trade relative to policy decisions has a potentially important impact on the welfare evaluation of monetary policy at the individual country level. If asset trade in the initial period takes place before the announcement of policy, a national policymaker can choose a policy rule which reduces the work effort of households in the policymaker’s country in the knowledge that consumption is fully insured by optimally chosen international portfolio positions. But if asset trade takes place after the policy announcement, this insurance is absent and households in the policymaker’s country bear the full consumption consequences of the chosen policy rule. The welfare incentives faced by national policymakers are very different between the two cases. Numerical examples confirm that asset market timing has a significant impact on the optimal policy rule.

Microstructure Order Flow: Statistical and Economic Evaluation of Nonlinear Forecasts

In this paper we propose a novel empirical extension of the standard market microstructure order flow model. The main idea is that heterogeneity of beliefs in the foreign exchange market can cause model instability and such instability has not been fully accounted for in the existing empirical literature. We investigate this issue using two di¤erent data sets and focusing on out- of-sample forecasts. Forecasting power is measured using standard statistical tests and, additionally, using an alternative approach based on measuring the economic value of forecasts after building a portfolio of assets. We nd there is a substantial economic value on conditioning on the proposed models.

Transaction Costs and Institutions

This paper proposes a simple framework for understanding endogenous transaction costs - their composition, size and implications. In a model of diversification against risk, we distinguish between investments in institutions that facilitate exchange and the costs of conducting exchange itself. Institutional quality and market size are determined by the decisions of risk averse agents and conditions are discussed under which the efficient allocation may be decentralized. We highlight a number of differences with models where transaction costs are exogenous, including the implications for taxation and measurement issues.

Forecasting the European Carbon Market

In an effort to meet its obligations under the Kyoto Protocol, in 2005 the European Union introduced a cap-and-trade scheme where mandated installations are allocated permits to emit CO2. Financial markets have developed that allow companies to trade these carbon permits. For the EU to achieve reductions in CO2 emissions at a minimum cost, it is necessary that companies make appropriate investments and policymakers design optimal policies. In an effort to clarify the workings of the carbon market, several recent papers have attempted to statistically model it. However, the European carbon market (EU ETS) has many institutional features that potentially impact on daily carbon prices (and associated nancial futures). As a consequence, the carbon market has properties that are quite different from conventional financial assets traded in mature markets. In this paper, we use dynamic model averaging (DMA) in order to forecast in this newly-developing market. DMA is a recently-developed statistical method which has three advantages over conventional approaches. First, it allows the coefficients on the predictors in a forecasting model to change over time. Second, it allows for the entire fore- casting model to change over time. Third, it surmounts statistical problems which arise from the large number of potential predictors that can explain carbon prices. Our empirical results indicate that there are both important policy and statistical bene ts with our approach. Statistically, we present strong evidence that there is substantial turbulence and change in the EU ETS market, and that DMA can model these features and forecast accurately compared to conventional approaches. From a policy perspective, we discuss the relative and changing role of different price drivers in the EU ETS. Finally, we document the forecast performance of DMA and discuss how this relates to the efficiency and maturity of this market.

The relationship between public education expenditure and economic growth: The case of India

The paper reviews the theoretical and the empirical case for public investment in education in India. Though the theoretical literature provides a backing for such a policy, the empirical literature fails to find a robust relation between education expenditure and growth. Expenditure on education is a necessary but not a sufficient condition for growth. It seems that the effectiveness of education expenditure depends on the institutional and labour market characteristics of the economy. The effectiveness of education investments also depends on other factors such as trade openness. Due to these aforesaid factors, we argue that the empirical relation between education expenditure and growth for India has been inconsistent.

Nominal Stability and Financial Globalization

Over the past four decades, advanced economies experienced a large growth in gross external portfolio positions. This phenomenon has been described as Financial Globalization. Over roughly the same time frame, most of these countries also saw a substantial fall in the level and variability of inflation. Many economists have conjectured that financial globalization contributed to the improved performance in the level and predictability of inflation. In this paper, we explore the causal link running in the opposite direction. We show that a monetary policy rule which reduces inflation variability leads to an increase in the size of gross external positions, both in equity and bond portfolios. This appears to be a robust prediction of open economy macro models with endogenous portfolio choice. It holds across different modeling specifications and parameterizations. We also present preliminary empirical evidence which shows a negative relationship between inflation volatility and the size of gross external positions.

Policy Labels and Investment Decision-making

Much attention in recent years has turned to the potential of behavioural insights to improve the performance of government policy. One behavioural concept of interest is the effect of a cash transfer label on how the transfer is spent. The Winter Fuel Payment (WFP) is a labelled cash transfer to offset the costs of keeping older households warm in the winter. Previous research has shown that households spend a higher proportion of the WFP on energy expenditures due to its label (Beatty et al., 2011). If households interpret the WFP as money for their energy bills, it may reduce their willingness to undertake investments which help achieving the same goal, such as the adoption of renewable energy technologies. In this paper we show that the WFP has distortionary effects on the renewable technology market. Using the sharp eligibility criteria of the WFP in a Regression Discontinuity Design, this analysis finds a reduction in the propensity to install renewable energy technologies of around 2.7 percentage points due to the WFP. This is a considerable number. It implies that 62% of households (whose oldest member turns 60) would have invested in renewable energy but refrain to do so after receiving the WFP. This analysis suggests that the labelling effect spreads to products related to the labelled good. In this case, households use too much energy from sources which generate pollution and too little from relatively cleaner technologies.