Place-Based Policies and Nowcasting

There is a growing need to gauge local economic activity in real time. Localised economic challenges have been emphasised in the wake of the COVID-19 pandemic. Real-time trackers (such as OECD trackers) and other nowcasting applications typically correspond to national or highly aggregated regions. In this discussion paper, we briefly explore how unconventional data might be used to produce nowcasts of local economies. We argue that in the absence of traditional nowcasting metrics, efforts to nowcast local economies need a local perspective, with data capture tailored to address heterogeneity across three domains: (1) resources, (2) people and (3) life.     

Nowcasting Indonesia

We produce predictions of the current state of the Indonesian economy by estimating a dynamic factor model on a dataset of 11 indicators (followed closely by market operators) over the 2002–2014 period. Besides the standard difficulties associated with constructing timely indicators of current economic conditions, Indonesia presents additional challenges typical to emerging market economies where data are often scant and unreliable. By means of a pseudo-real-time forecasting exercise, we show that our model outperforms univariate benchmarks, and it does comparably well with predictions of market operators. Finally, we show that when quality of data is low, a careful selection of indicators is crucial for better forecast performance.     

Nowcasting Key Australian Macroeconomic Variables

Forecasts are relied upon as a guide to what future outcomes for the economy might be. However, it is also important to estimate what is happening in the economy now or has taken place in the recent past. This is where ‘nowcasts’ come in. In this article, I describe what nowcasting is, why it can be a useful tool for macroeconomists as well as present daily nowcasts of key Australian macroeconomic variables, including GDP growth, inflation and the unemployment rate.     

Nowcasting causality in mixed frequency vector autoregressive models

This paper introduces nowcasting causality as the mixed-frequency version of instantaneous causality. We analyze the relationship between nowcasting and Granger causality in a mixed-frequency VAR and illustrate its impact on the significance of high-frequency variables in mixed-frequency conditional models.     

Nowcasting sales growth of manufacturing companies in India

The performance of private corporate sector is used as an important demand indicator for monetary policy making. As these data are received with a lag, assessing and monitoring of corporate sales on a real-time basis poses a significant challenge to policy makers in India. In this context, this article attempts to nowcast quarterly sales growth of Indian manufacturing companies and GDP growth of India using dynamic factor modelling framework. A multiple-level framework through turning point analysis and elastic net structure is used to overcome the overfitting problem during variable selection. Empirical results show improvement in forecast accuracy for one quarter ahead nowcast using 3-factor and 4-factor models over the benchmark model. However, absolute dominance of 3-factor models over 4-factor models was not established. As such, the article has proposed a forecast combination technique to nowcast sales growth of manufacturing companies in India.     

Nowcasting Chinese GDP: information content of economic and financial data

This article applies the factor model proposed by Giannone, Reichlin, and Small (2005 Giannone, D., Reichlin, L. and Small, D. 2005. “Nowcasting GDP and inflation: The real time information content of macroeconomic data release”. In Finance and Economic Discussion Series 2005–42, Washington, DC: Board of Governors of the Federal Reserve System.  [Google Scholar]) on a large data set to nowcast (i.e. current-quarter forecast) the annual growth rate of China's quarterly GDP. The data set contains 189 indicator series of several categories, such as prices, industrial production, fixed asset investment, external sector, money market, and financial market. This article also applies Bai and Ng's criteria (2002) to determine the number of common factors in the factor model. The identified model generates out-of-sample nowcasts for China's GDP with smaller mean-squared forecast errors than those of the random walk benchmark. Moreover, using the factor model, we find that interest rate data is the single most important block of information to improve estimates of current-quarter GDP in China. Other important blocks are consumer and retail prices data and fixed asset investment indicators.     

Nowcasting National GDP Growth Using Small Business Sales Growth

This study shows that the Xero Small Business Index (XSBI) sales growth data can be used to predict the same period's national nominal GDP growth, with high accuracy, in the United Kingdom, Australia and New Zealand. Findings show that XSBI sales growth can predict the same month's GDP growth around two weeks earlier than the official release in the United Kingdom. On the other hand, the three-month average of the XSBI sales growth can predict the same quarter's GDP growth, six weeks earlier than the official release in New Zealand and five weeks earlier than the official release in Australia.     

Nowcasting norwegian GDP: the role of asset prices in a small open economy

This article finds that asset prices on Oslo Stock Exchange is the single most important block of data to improve estimates of current quarter GDP in Norway. We use an approximate dynamic factor model that is able to handle new information as it is released, thus the marginal impact on mean square nowcasting error can be studied for a large number of variables. We use a panel of 148 non-synchronous variables. The high informational content in asset prices is explained by reference to the small size of companies on Oslo Stock Exchange and the small and open nature of the Norwegian economy.     

Nowcasting the French index of industrial production: A comparison from bridge and factor models

Governments and central banks need to have an accurate and timely assessment of indicators for the current month, as this is essential for providing a reliable and early analysis of the current economic situation. The index of industrial production (IIP) is probably the most important and widely analyzed monthly indicator, given the relevance of the manufacturing activity as a driver of the whole business cycle. This paper presents a series of models conceived to forecast the current French monthly IIP, based on regression models and dynamic factor models. The combination of these two approaches allows selecting economically relevant explanatory variables among a large data set. In addition, a rolling forecast study is carried out to assess the forecasting performance of the estimated models, using predictive ability and model confidence set tests. This latter allows getting several models displaying equivalent forecasting performance and therefore gives robustness to the forecasting exercise rather than to base the forecasting analysis only on one model.     

中国宏观经济总量的实时预报与短期预测——基于混频数据预测模型的实证研究

季度GDP的走势与波动不仅会影响政府的财政收支、企业的盈利和财务状况,甚至还会影响家庭和个人的收入与支出,是宏观经济总量预报、预测与分析的重中之重。传统的宏观经济总量预测模型是基于同频数据进行的,高频和超高频数据必需处理为低频数据,这不仅忽略了高频数据信息的变化,还影响了模型预报和预测的及时性,降低了模型的预测精度。本文将混合数据抽样模型(MIDAS)用于中国季度GDP的预报和预测,实证研究表明,出口是造成我国金融危机时期经济增长减速的主要因素,MIDAS模型在中国宏观经济总量的短期预测方面具有精确性的比较优势,在实时预报方面具有显著的可行性和时效性。     

Teamwork,monitoring and absence

We present a model showing that firms with interdependent worker productivity (team production) have a higher cost of absence and as a consequence will spend additional resources on monitoring absence. As a result, firms with team production should have lower absence rates, all else equal. Using the Workplace Employment Relations Survey (UK), we are the first to estimate each of these related associations showing that absence has a greater cost in the face of team production, that firms with team production engage in greater monitoring and that firms with team production have reduced absence.     

Reputation,monitoring, and effort

This paper studies the impact of strategic monitoring on reputation building, focusing in particular on models of the principal-agent type. The main result is that the principal always will monitor risk-neutral agents more closely early in the game, while such agents may or may not work harder as the game progresses, depending on their initial reputation. If agents are sufficiently risk-averse, they will always work harder early in the game, whereas the principal may or may not monitor such agents more closely as the game progresses.     

Collateral,labour monitoring and banking accelerator

This paper derives the determination of external finance premium (EFP ) in the context of banking sector profit maximisation behaviour. EFP/credit spread stems from the managerial cost, associated with the intermediation process, of factor payments to collateral and labour services. The stake of entrepreneurs is relevant to determine the EFP on two grounds: (a) the ratio of entrepreneurial net wealth to collateral value influences the total managerial cost; and (b) entrepreneurs' net worth (fraction of total collateral) helps mitigate the EFP from extracting rebate from collateral service. Based on these, we can derive an observationally similar relationship between EFP and entrepreneurial leverage, as in previous studies. This provides a rationale for us to understand the financial friction from a novel perspective. Besides the leverage ratio, the EFP is shown to be determined also by the resource cost of financial intermediation, for which the model generates a mechanism that contains broader ingredients in determining the behaviour of EFP .     

Private monitoring in auctions

We study infinitely repeated first-price auctions in which a bidder only learns whether or not he won the object. While repetition of the stage-game equilibrium is the unique Nash equilibrium in public strategies, with patient bidders there are simple Nash equilibria in private strategies that improve on bid rotation. Sequential rationality is appropriately captured by essentially perfect Bayesian equilibrium (EPBE), which ignores behavior after irrelevant histories. Our main result is the construction of EPBEa that improve upon bid rotation. Assuming symmetry, the exclusionary schemes of Skrzypacz and Hopenhayn [Tacit collusion in repeated auctions, J. Econ. Theory 114 (2004), 153–169], including asymptotically efficient ones, are supported as EPBEa.     

Biodiversity,natural resource accounting and ecological monitoring

The role that natural resource accounting and ecological monitoring can play in conserving biological diversity is discussed. There exists a widespread view that modifications to national income accounting procedures are crucial to the pursuit of sustainability and particularly the protection of biodiversity. However, we argue that the availability of biologically-adjusted national income figures would not, of itself, be likely to contribute significantly to the protection of biological resources. The conservation of biodiversity requires, among other things, a significantly improved understanding of the nature of environmental changes arising from imposed management regimes and the effects that these changes have on the persistence of biodiversity. On this basis, and in the context of sustainable development, we suggest that ecological monitoring should take priority over the generation of economic data.In many regions of the world sufficient ecological knowledge is available to design and implement integrated monitoring networks that can be used to track the status of many components of biodiversity and inform decisions taken over their management. We outline how this might be undertaken using a hierarchical and prioritised approach aimed, pragmatically, in the first instance at helping to preserve those ecosystems, communities and species which are perceived to be most threatened. Some emphasis is given to the Australian situation because it is the only rich megadiversity nation and it is at the forefront of the development of scientific techniques that can be used to help design soundly-based and cost-effective monitoring programs.We acknowledge the useful comments of two referees, and claim exclusive property rights in remaining errors.     

期货逼仓机理及监控研究

如何监控逼仓事件的发生、妥善处理逼仓事件,是国内外期货界人士一直重视的课题。本文通过调查和收集数据,研究了国内近年来典型的逼仓案例,探讨了期货逼仓的市场条件及发生过程,分析了其发生机理和危害性。在此基础上,重点研究了影响期货风险的主要因素,建立监控指标体系,并对指标进行合理性和相关性测试。阐述了中国期货市场必须建立防范期货逼仓的风险管理体制,提出了相应的对策。