Engineering the Financialization of Urban Entrpreneurialism: The JESSICA Urban Development Initiative in the European Union

Urban entrepreneurialism and neoliberal urban governance are assuming new forms under finance‐dominated accumulation. We examine and contribute to theorizing the mechanisms through which urban governance is financialized, taking as a case study JESSICA, one of the European Union's initiatives to implement an ‘urban sensitive’ policy for sustainable and integrated development. Like other initiatives promoting financialization, JESSICA deploys the logic of finance to select and fund urban social initiatives and development projects on the basis of their potential return on investment (ROI). Understanding this process requires placing questions of political economy—how urban governance is shaped by the broader political‐economic context—with questions of governmentality—how stakeholders are enrolled in and come to take for granted new governance initiatives. Following the multi‐scalar institutional infrastructure is crucial to understanding how this works. Taking a relational multi‐scalar approach, we trace how changes at the supranational scale filter down to shape urban policy selection and performance in Sofia, Bulgaria, where we document how ROI calculations conflict with social welfare priorities. Contrasts between the trajectory of financialization of urban governance in the European Union and the United States demonstrate how this is geographically variegated, shaped by the broader context/conjuncture within which such financialization is embedded.     

Forecasting the UK economy with a medium-scale Bayesian VAR

We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England’s DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR’s point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.     

Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?

This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.     

Panel LM unit root tests with level and trend shifts

This paper considers a Lagrange multiplier (LM) based panel unit root test that allows for heterogeneous structural breaks in both the intercepts and slopes of a series. We note that many popular time series variables are likely to exhibit changing means and/or trends over time. Given that the usual tests will depend on the nuisance parameters indicating the locations of the trend breaks, we adopt a transformation procedure that makes our new panel unit root tests invariant to the nuisance parameters. To illustrate the importance of the power gain provided by our test, we examine the convergence hypothesis using relative ratios of per capita health care expenditures in 20 OECD countries. Our results provide evidence that the convergence hypothesis is supported.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

A Bayesian analysis of a variance decomposition for stock returns

We apply Bayesian methods to study a common vector autoregression (VAR)-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy, which involves expressing beliefs about the components of the variance decomposition. Previous Bayesian work elicited priors from the difficult-to-interpret parameters of the VAR. With a commonly used data set, we find that the posterior standard deviations for the variance decomposition based on these previously used priors, including “non-informative” limiting cases, are much larger than classical standard errors based on asymptotic approximations. Therefore, the non-informative researcher remains relatively uninformed about the variance decomposition after observing the data. We show the large posterior standard deviations arise because the “non-informative” prior is implicitly very informative in a highly undesirable way. However, reasonably informative priors using our elicitation method allow for much more precise inference about components of the variance decomposition.     

The Structural Relation Between Mortgage and Market Interest Rates

This paper analyzes the dynamic relationship between primary and secondary mortgage markets and the short-term and long-term market interest rates. Using a series of monthly data on fixed rate mortgage rates and GNMA rates, we explore the dependence and speed of adjustment in these primary and secondary mortgage rates to each other as well as to the long and short-term government rates. The results indicate that residential mortgage rates in general, appear to follow the long-term rate and are not very sensitive to movements in the short-term interest rate.     

The effect of exchange rate changes on trade balances in the short and long run

Using generalized impulse response functions, this study tests for the trade J‐curve for three transitional central European countries – the Czech Republic, Hungary, and Poland – in their bilateral trade with respect to Germany. Our findings suggest that for each country there are some characteristics associated with a J‐curve effect: after a (real or nominal) depreciation the export‐to‐import ratio briefly drops to below its initial value within a few months and then rises to a long run equilibrium value higher than the initial one.     

中国和新加坡产业内贸易与规模经济关系的协整分析

中国和新加坡产业内贸易与规模经济存在着一种长期的均衡关系,新加坡生产企业的规模经济对产业内贸易的推动作用大于中国,中国和新加坡生产企业的规模经济与产业内贸易存在单向因果关系,即规模经济促进产业内贸易.     

AN EMPIRICAL EXAMINATION OF RELATIONSHIP MAGNITUDE

Based upon a review of the extant literature, it is proposed that the structure of an interorganizational relationship is composed of relationship type and the under‐researched construct of relationship magnitude. Specifically, it is hypothesized that relationship magnitude, a second order construct composed of trust, commitment, and dependence, affects relationship type, which affects the perception of value of the relationship. The results of a survey analyzed through structural equation modeling support these hypotheses.