Did taxes,decrees or credibility drive money? Early nineteenth century Finland from a chartalist perspective

Chartalist theories assume the government determines the currency used by the public. Finland’s experience following the Russo-Swedish war in 1808–1809 would seem to contradict the chartalist view. Having become a Grand Duchy under Russia, the Finnish Government sought to replace Swedish riksdalers in circulation with roubles. However, due to a resilient trade surplus with Sweden and the resulting flood of Swedish money into Finland, bans on the riksdaler were largely ineffective. Taxation proved a particularly clumsy tool for leveraging the switch to roubles. Taxpayers almost forced the government to accept payments in a foreign currency. Even the government had to use Swedish money. Issuing roubles was of limited use. As a result, the rouble failed to establish itself as Finland’s main currency until the introduction of a silver standard in 1840–1842.     

COMPARING PPP WITH TRADITIONAL PROCUREMENT: THE CASE OF SCHOOLS PROCUREMENT IN IRELAND

Advocates of public‐private partnerships (PPPs) argue that they can deliver public infrastructure more efficiently than traditional procurement through timelier completion and superior value for money. Despite these claims comparative analysis of the performance of both procurement methods has received scant attention in the PPP literature to date. This paper addresses this issue by providing an in‐depth, case‐based comparison of PPP versus traditional procurement in the schools sector in Ireland. Through detailed semi‐structured interviews with key stakeholders and an examination of the available documentation, we assess whether the key objectives of using PPP have been achieved. Overall, we find no evidence that PPP leads to faster delivery of infrastructure when the overall procurement process from contract notice to delivery is accounted for. In addition, we find only limited evidence to suggest that PPP results in better value for money.     

Magic mirror in my hand … How trade mirror statistics can help us detect illegal financial flows

Misreporting tricks of different sorts applied to the transfer of goods between different countries are typically exploited by criminals worldwide for money laundering ends. The main international anti‐money laundering organisations started paying attention to this phenomenon, dubbed “trade‐based money laundering” (TBML), a long time ago, but the failure to develop appropriate analytical tools has reportedly dogged preventive actions. Nonetheless, literature has widely advocated the possibility that the analysis of inconsistencies in mirrored bilateral trade data could provide some help. By building on previous contributions in the field, this work sets up a model factoring in the main structural determinants of discrepancies between mirrored data concerning Italy's 2010 to 2013 external trade at a highly detailed (6‐digit) level of goods classification for each partner country. Point estimates of freight costs are used to net each observation of the corresponding cif/fob discrepancy. The regression estimates are then deployed in order to compute TBML risk indicators at a country/4‐digit product level. Based on the indicators, rankings of countries and product lines can be compiled, which may be used for a risk‐driven search of potential illegal commercial transactions.     

Re‐vitalizing money demand in the Euro area. Still valid at the zero‐lower bound

The analysis of monetary developments has always been a cornerstone of the ECB's monetary analysis and, thus, of its overall monetary policy strategy. In this respect, money demand models provide a framework for explaining monetary developments and assessing price stability over the medium term. It is a well‐documented fact in the literature that, when interest rates are at the zero‐lower bound, the analysis of money stocks become even more important for monetary policy. Therefore, this paper re‐investigates the stability properties of M3 demand in the euro area in the light of the recent economic crisis. A cointegration analysis is performed over the sample period 1983 Q1 and 2015 Q1 and leads to a well‐identified model comprising real money balances, income, the long‐term interest rate and the own rate of M3 holdings. The specification appears to be robust against the Lucas critique of a policy dependent parameter regime, in the sense that no signs of breaks can be found when interest rates reach the zero‐lower bound. Furthermore, deviations of M3 from its equilibrium level do not point to substantial inflation pressure at the end of the sample. Excess liquidity models turn out to outperform the autoregressive benchmark, as they deliver more accurate CPI inflation forecasts, especially at the longer horizons. The inclusion of unconventional monetary policy measures does not contradict these findings.     

中国的金融市场开发与借款证券化

在当今社会，市场对金融运行的压力越来越大，传统的融资方式已难以满足投资者的需要。一种新的金融形式——贷款证券化，使资金拥有者可以通过这一渠道将资金转移到贷款者手中。通过这种形式，可以很好地解决当今社会许多融资难的问题。目前，这种融资形式正在引起我国许多业界人士的注意，这种形式如果能够在我国的金融体系中得到完善，将会极大地促进我国的经济建设，也能很好地解决我国投融资体系中存在的诸多现实问题。     

Why Money Growth Determines Inflation in the Long Run: Answering the Woodford Critique

Woodford argues that it is not appropriate to regard inflation in the steady state of New Keynesian models as determined by steady‐state money growth. Woodford instead argues that the intercept term in the monetary authority's interest rate policy rule determines steady‐state inflation. In this paper, I offer an alternative interpretation of steady‐state behavior, according to which it is appropriate to regard steady‐state inflation as determined by steady‐state money growth. The argument relies on traditional interpretations of the central bank's power in the long run and appeals to model properties that are common to textbook and New Keynesian analysis. According to this argument, the only way the central bank can control interest rates in the long run is via affecting inflation, and its only means available for determining inflation is by determining the money growth rate.     

对大学生产生重大影响的社会思潮

西方自由主义、拜金主义、享乐主义、个人主义、功利主义等是影响当代大学生思想的主要社会思潮。大学生易受不良思潮影响的原因在于缺乏历史知识,政治理论学习不深入,同时受西方思想文化的长期影响。所以要正确引导学生自觉学习政治理论,系统全面了解社会发展史,树立正确的人生观和价值观。同时网络、影视、报刊等媒体要有一个正确的导向,给大学生成长营造出一个好的成长环境。     

对加拿大货币需求的数量分析

在特定的经济条件下，全社会货币需求量以及这个量的变动规律，是一国政府制定并执行货币政策和财政政策时所要考虑的重要参数。战后以来，西方国家政府一般是通过货币政策和财政政策的执行，最终影响产出量和就业水平。分析影响货币需求变动的因素及其变量之间的数量关系，是正确地预测货币需求变动的关键。加拿大的货币需求与其相关的经济因素之间的关系；加拿大货币供求与经济增长之间的关系。     

Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ

Bayesian multiple imputation (MI) has become a highly useful paradigm for handling missing values in many settings. In this paper, I compare Bayesian MI with other methods – maximum likelihood, in particular—and point out some of its unique features. One key aspect of MI, the separation of the imputation phase from the analysis phase, can be advantageous in settings where the models underlying the two phases do not agree.     

The Multilevel Approach to Repeated Measures for Complete and Incomplete Data

Repeated measurements often are analyzed by multivariate analysis of variance (MANOVA). An alternative approach is provided by multilevel analysis, also called the hierarchical linear model (HLM), which makes use of random coefficient models. This paper is a tutorial which indicates that the HLM can be specified in many different ways, corresponding to different sets of assumptions about the covariance matrix of the repeated measurements. The possible assumptions range from the very restrictive compound symmetry model to the unrestricted multivariate model. Thus, the HLM can be used to steer a useful middle road between the two traditional methods for analyzing repeated measurements. Another important advantage of the multilevel approach to analyzing repeated measures is the fact that it can be easily used also if the data are incomplete. Thus it provides a way to achieve a fully multivariate analysis of repeated measures with incomplete data. This revised version was published online in June 2006 with corrections to the Cover Date.