ALTERNATIVE WEIGHTING APPROACHES TO COMPUTING INDEXES OF ECONOMIC ACTIVITY

This paper compares the weighting schemes in the traditional, principal component and dynamic factor approaches to summarizing information from a number of component variables. To facilitate the comparison, we propose a framework to discuss the approaches with respect to their implied loadings in a latent variable model. We also propose a way to transform the dynamic factor index into an analogous index which is a weighted average of the components. The framework shows the strengths and weakness of the alternative weighting schemes and the sense in which the dynamic factor approach has the advantage of capturing both the significance and the variability of the components.     

Upzoning and value capture: How U.S. local governments use land use regulation power to create and capture value from real estate developments

The public sector can harness its authority to control land uses to secure valuable public benefits from real estate developments. This paper investigates how five major U.S. cities—Boston, Chicago, New York, San Francisco, and Seattle—are using their land use regulation powers to create and capture value for the public benefit. An analysis of the zoning and entitlement processes of the 20 largest real estate development projects in each city reveals that value has been captured from all 100 projects. Furthermore, these cities implicitly differentiated value capture into two distinct components: value creation and value capture. Among the 100 projects, cities created value for 90 projects by allowing greater density and height—a practice often referred to as “upzoning.” Distinguishing such upzoning incidences from traditional land use exaction tools is important because the added value gives local governments greater legitimacy in asking for public benefits. The experience of the five cities further revealed that value capture strategies can be customized to adapt to unique regulatory, political, and cultural contexts. Lastly, despite the fact that the majority of the upzoned projects increased density and height through project-specific negotiations, none of the cities had clear standards or evaluation frameworks for determining: how much value was created, what can be asked for in return, and who should benefit from the value captured. Cross-national scholarship on value capture can be leveraged to address these important questions.     

The role of accelerators in firm survival: An fsQCA analysis of Italian startups

Accelerators are a recent yet rapidly growing phenomenon within entrepreneurial ecosystems. The distinctive characteristics exhibited by accelerators, relative to previous incubation models, imply that accelerators may play a different role and have a different impact on the survival rates of participating firms. In this study, we explore the relationship between participation in an accelerator program and firm survival using fuzzy-set qualitative comparative analysis (fsQCA) with key variables related to firm survival. We analyze 38 accelerated startups from five Italian accelerators and a control group of 38 non-accelerated Italian startups. Our findings support the business accelerator literature that regards accelerators as a new and distinct generation of business incubators. Our results suggest that participation in accelerator programs on its own does not influence firm survival. However, we found a relationship between firm survival and accelerated technology-based firms that do not export and between firm survival and accelerated firms in the service sector with a small team that do not export. We conclude that factors affecting the survival of accelerated firms are different from factors affecting the survival of incubated firms, providing further evidence of the characteristics that distinguish accelerators from incubators.     

Relationship between city size and firm productivity – A new interpretation using the Chinese experience

This paper contributes to the literature on the relationship between city size and firm productivity by focusing on agglomeration, selection (market competition), and sorting (presence of firms with diverse productivity) effects using Chinese firm-level data for 1998–2013. Contrary to the existing literature, our parametric regression estimates from nearly two million firms show that when the selection effect is controlled, productivity advantage in big cities is reversed. This outcome is explained through a quantile regression showing the existence of left-sided sorting (inefficient firms sort themselves to larger cities) in big cities which is not captured in existing empirical literature. We further find that (1) left-sided sorting is stronger in exporters than non-exporters; (2) is also generated mainly in enterprises with high asset-liability ratios; and (3) selection has a positive effect on firm productivity, suggesting that market competition is key in an explanation of the rapid growth of big cities in China.     

Expanding airport capacity of cities under uncertainty: Strategies to mitigate congestion

Airport capacity constraints are increasingly challenging the growth of air traffic. At the same time, decision-making about airport capacity investments is extremely complex, involving trade-offs. This paper’s objective is to optimise a privately owned airport system’s capacity investment decision in a city under demand uncertainty. Next to the investment size, our real options model incorporates the timing of the investment, as well as the cost of congestion. The results reveal that the larger a city’s initial airport capacity, the smaller its investment will relatively be and the lower the occupancy rate threshold at which investment will take place. We also show that, in case of a higher demand growth combined with more demand uncertainty, the city will benefit from a significantly larger investment, but made later at a higher occupancy rate. In this case, cities with a small initial capacity will sometimes even more than double current capacity. Higher airport charges and an increase in non-aeronautical revenues both lead to a later investment in more capacity, due to the increased project attractiveness. An increase in congestion costs results in a larger investment made earlier, in order to eliminate delays. Airport operational cost and capacity holding cost increases both lead to smaller investments.     

Impact of macroeconomic surprises on the Brazilian yield curve and expected inflation

This study investigates how unexpected announcements in Brazilian and U.S. macroeconomic indicators affect the term structure of nominal interest rates, as well as implicit inflation expectations and real interest rates. Using daily data from March 2005 to December 2012, we employ an extended Vector Error Correction Model to take into account nonstationarity and the long-term equilibrium among different maturities of those curves. We found empirical evidence that macroeconomic surprises, domestic (Brazilian) and external (U.S. American), which lead the market to believe that there might be a higher risk of inflation or an overheated economy, raise nominal interest rates, implicit expected inflation and real interest rates. Surprisingly, in relation to the efficient-market hypothesis, we found that some macroeconomic surprises have a lagged effect on the yield curves. We also tested the impact of the global financial crisis of 2007–09 and found that the crisis affected significantly the direction and magnitude of the responses to macroeconomic news.     

Impact of electronic road pricing on real estate prices in Singapore

Since 1998, Singapore has had an Electronic Road Pricing (ERP) system set up with a network of toll gantries to tax vehicles entering designated areas in the city center during peak hours. Using the congestion rate hike with effect from November 1, 2010 as an exogenous shock, we test the effects of the ERP rate hike on retail, office and residential real estate prices. The results show that the November 2010 congestion toll rate increases cause a 19% drop in retail real estate prices within the cordon ERP areas relative to retail real estate prices outside the cordon ERP areas. The results are statistically and economically significant. However, the toll rate hike has no significant impact private office and residential real estate within cordoned ERP areas. The robustness and falsification tests could not reject the negative effects associated with the toll rate hike on retail real estate prices.     

Assessing targeted macroprudential financial regulation: The case of the 2006 commercial real estate guidance for banks

In January 2006, federal regulators issued guidance requiring banks with specific high concentrations of commercial real estate (CRE) loans to tighten managerial controls. This paper shows that banks with concentrations in excess of the thresholds set in the guidance subsequently experienced slower growth in their CRE portfolios than can be explained by changes in bank or economic conditions. Moreover, banks above the CRE thresholds tended to have slower commercial and industrial loan growth but faster household loan growth following issuance of the guidance. The results highlight the potentially broad influence that portfolio-based macroprudential regulation might have on bank behavior.     

Decision-making in incomplete markets with ambiguity—a case study of a gas field acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian Motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore, we use Gaussian generalized autoregressive score (GAS) and GARCH models, extending them to Student’s t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. As a result, markets are incomplete which makes preference free pricing impossible and thus standard option pricing methodology inapplicable. Therefore, we parametrize the investor’s risk preference and use utility indifference pricing techniques. We use Least Squares Monte Carlo simulations as a dimension reduction technique in solving the resulting stochastic dynamic programming problems. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time-dependent stochastic structures.     

Monetary policy,endogenous transactions,and financial market segmentation

An endogenous financial market segmentation model is constructed to explore the role of costly credit as a medium of exchange in the monetary policy elasticity of financial market activity. Against inflation risk, credit is an alternative insurance device to a cash transfer from the financial market. In equilibrium, credit reduces the financial market activity rate. Monetary policy has redistributive effects across economic individuals. Inflation may not tax financial market non-participants. However, it may tax financial market participants by increasing the financial market activity rate. Welfare may increase and the optimal money growth rate can be positive.