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IT-driven trading innovations offer institutional investors alternative trading channels to broker delegated order handling. Motivated by the impact on intermediation relationships in securities trading and the adoption rate of such trading channels, the new option of self-directed order handling is analyzed. To capture the prerequisites for institutional investors to insource their order handling, an order-channel management (OCM) framework is introduced. It is based on a structural approach to account for the increasing complexity in comparison to traditional intermediary services. Drivers for the adoption of an OCM framework are investigated from the strategic perspective. Operational OCM is based on the business value of IT analysis of distinct trading innovations. It includes smart order router technology, low latency technology as an upgrade for existing IT-driven trading channels as well as negotiation dark pools, representing alternative trading venues. Evidence that all investigated IT-driven trading innovations generate additional business value is provided as one result. However, it is also shown that they exhibit entry barriers tightly related to investor size. Further, Task-Technology Fit is proven to be the major driver for the adoption decision. Consequently, IT-driven trading innovations should increase trading control, satisfy high anonymity and varying urgency demands.
There is a growing debate about complementing the European Monetary Union by a more comprehensive fiscal union. Against this background, this paper emphasizes that there is a trade-off in designing a system of fiscal transfers ("fiscal capacity") in a union between members of different size. A system cannot guarantee symmetric treatment of members and simultaneously ensure a balanced budget. We compute hypothetical transfers for the Eurozone members from 2001 to 2012 to illustrate this trade-off. Interestingly, a symmetric system that treats shocks in small and large countries symmetrically would have produced large budgetary surpluses in 2009, the worst year of the financial crisis.
The Federal Reserve’s muddled mandate to attain simultaneously the incompatible goals of maximum employment and price stability invites short-term-oriented discretionary policymaking inconsistent with the systematic approach needed for monetary policy to contribute best to the economy over time. Fear of liftoff—the reluctance to start the process of policy normalization after the end of a recession—serves as an example. Causes of the problem are discussed, drawing on public choice and cognitive psychology perspectives. The Federal Reserve could adopt a framework that relies on a simple policy rule subject to periodic reviews and adaptation. Replacing meeting-by-meeting discretion with a simple policy rule would eschew discretion in favor of systematic policy. Periodic review of the rule would allow the Federal Reserve the flexibility to account for and occasionally adapt to the evolving understanding of the economy. Congressional legislation could guide the Federal Reserve in this direction. However the Federal Reserve may be best placed to select the simple rule and could embrace this improvement on its own, within its current mandate, with the publication of a simple rule along the lines of its statement of longer-run goals.
This paper investigates the effect of a change in informational environment of borrowers on the organizational design of bank lending. We use micro-data from a large multinational bank and exploit the sudden introduction of a credit registry, an information-sharing mechanism across banks, for a subset of borrowers. Using within borrower and loan officer variation in a difference-in-difference empirical design, we show that expansion of credit registry led to an improvement in allocation of credit to affected
borrowers. There was a concurrent change in the organizational structure of the bank that involved a dramatic increase in delegation of lending decisions of affected borrowers to loan officers. We also find a significant expansion in scope of activities of loan officers who deal primarily with affected borrowers, as well as of their superiors. There is suggestive evidence that larger banks in the economy were better able to implement similar changes as our bank. We argue that these patterns can be understood within the framework of incentive-based and information cost processing theories. Our findings could help rationalize why improvements in the information environment of borrowers may be altering the landscape of lending by moving decisions outside the boundaries of financial intermediaries.
This chapter outlines the conditions under which accounting-based smoothing can be beneficial for policyholders who hold with-profit or participating payout life annuities (PLAs). We use a realistically-calibrated model of PLAs to explore how alternative accounting techniques influence policyholder welfare as well as insurer profitability and stability. We find that accounting smoothing of participating life annuities is favorable to consumers and insurers, as it mitigates the impact of short-term volatility and enhances the utility of these long-term annuity contracts.
We investigate the determinants of firms’ implicit insurance to employees, using a difference-in-difference approach: we rely on differences between family and non-family firms to identify the supply of insurance, and exploit variation in unemployment insurance across and within countries to gauge workers’ demand for insurance. Using a firm-level panel from 41 countries, we find that family firms feature more stable employment, greater wage flexibility and lower labor cost than non-family ones. Employment stability in family firms is greater, and the wage discount larger, in countries with more generous public unemployment insurance: private and public provision of employment insurance are substitutes.
We propose a multivariate dynamic intensity peaks-over-threshold model to capture extreme events in a multivariate time series of returns. The random occurrence of extreme events exceeding a threshold is modeled by means of a multivariate dynamic intensity model allowing for feedback effects between the individual processes. We propose alternative specifications of the multivariate intensity process using autoregressive conditional intensity and Hawkes-type specifications. Likewise, temporal clustering of the size of exceedances is captured by an autoregressive multiplicative error model based on a generalized Pareto distribution. We allow for spillovers between both the intensity processes and the process of marks. The model is applied to jointly model extreme returns in the daily returns of three major stock indexes. We find strong empirical support for a temporal clustering of both the occurrence of extremes and the size of exceedances. Moreover, significant feedback effects between both types of processes are observed. Backtesting Value-at-Risk (VaR) and Expected Shortfall (ES) forecasts show that the proposed model does not only produce a good in-sample fit but also reliable out-of-sample predictions. We show that the inclusion of temporal clustering of the size of exceedances and feedback with the intensity thereof results in better forecasts of VaR and ES.
Expectations of Sterling returning to Gold have been disregarded in empirical work on the US dollar – Sterling exchange rate in the early 1920s. We incorporate such considerations in a PPP model of the exchange rate, letting the probability of a return to gold follow a logistic function. We draw several conclusions: (i) the PPP model works well from spring 1919 to spring 1925; (ii) wholesale prices outperform consumer prices; (iii) allowing for a return to gold leads to a higher speed of adjustment of the exchange rate to PPP; (iv) interest rate differentials and the relative monetary base are crucial determinants of the expected return to gold; (v) the probability of a return to Gold peaked at about 72% in late 1924 and but fell to about 60% in early 1925; and (vi) our preferred model does not support the Keynes’ view that Sterling was overvalued after the return to gold.
Since the 1970s, the overarching view in the literature has been that a Phillips curve relationship did not exist in Ireland prior to the 1979 exchange rate break with Sterling. It was argued that, as a small open economy, prices were determined externally. To test this relationship, we study the determination of inflation between 1926 and 2012, a longer sample period than any previously used. We find that the difference between unemployment and the NAIRU is a significant determinant of inflation both in the full sample and in the subsamples spanning the periods before and after the Sterling parity link.
In this paper we assemble an annual data set on broad and narrow money, prices, real economic activity and interest rates in Ireland from a variety of sources for the period 1933-2012. We discuss in detail how the data set is constructed and what assumptions we have made to do so. Furthermore, we estimate a simple SVAR model to provide some empirical evidence on the behaviour of these time series. Money supply shocks appear to be the most important drivers of both money and prices. Interest rate shocks, which capture monetary policy, play an important role driving output and, of course, interest rates. The GDP shocks, which raise prices, seem of less importance.