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The lessons from QE and other 'unconventional' monetary policies - evidence from the Bank of England
(2011)
This paper investigates the effectiveness of the ‘quantitative easing’ policy, as implemented by the Bank of England in March 2009. Similar policies had been previously implemented in Japan, the U.S. and the Eurozone. The effectiveness is measured by the impact of Bank of England policies (including, but not limited to QE) on nominal GDP growth – the declared goal of the policy, according to the Bank of England. Unlike the majority of the literature on the topic, the general-to-specific econometric modeling methodology (a.k.a. the ‘Hendry’ or ‘LSE’ methodology) is employed for this purpose. The empirical analysis indicates that QE as defined and announced in March 2009 had no apparent effect on the UK economy. Meanwhile, it is found that a policy of ‘quantitative easing’ defined in the original sense of the term (Werner, 1994) is supported by empirical evidence: a stable relationship between a lending aggregate (disaggregated M4 lending, i.e. bank credit for GDP transactions) and nominal GDP is found. The findings imply that BoE policy should more directly target the growth of bank credit for GDP-transactions.
This paper compares the shareholder-value-maximizing capital structure and pricing policy of insurance groups against that of stand-alone insurers. Groups can utilise intra-group risk diversification by means of capital and risk transfer instruments. We show that using these instruments enables the group to offer insurance with less default risk and at lower premiums than is optimal for standalone insurers. We also take into account that shareholders of groups could find it more difficult to prevent inefficient overinvestment or cross-subsidisation, which we model by higher dead-weight costs of carrying capital. The tradeoff between risk diversification on the one hand and higher dead-weight costs on the other can result in group building being beneficial for shareholders but detrimental for policyholders.
Depending on the point of time and location, insurance companies are subject to different forms of solvency regulation. In modern regulation regimes, such as the future standard Solvency II in the EU, insurance pricing is liberalized and risk-based capital requirements will be introduced. In many economies in Asia and Latin America, on the other hand, supervisors require the prior approval of policy conditions and insurance premiums, but do not conduct risk-based capital regulation. This paper compares the outcome of insurance rate regulation and risk-based capital requirements by deriving stock insurers’ best responses. It turns out that binding price floors affect insurers’ optimal capital structures and induce them to choose higher safety levels. Risk-based capital requirements are a more efficient instrument of solvency regulation and allow for lower insurance premiums, but may come at the cost of investment efforts into adequate risk monitoring systems. The paper derives threshold values for regulator’s investments into risk-based capital regulation and provides starting points for designing a welfare-enhancing insurance regulation scheme.
Depending on the point of time and location, insurance companies are subject to different forms of solvency regulation. In modern regulation regimes, such as the future standard Solvency II in the EU, insurance pricing is liberalized and risk-based capital requirements will be introduced. In many economies in Asia and Latin America, on the other hand, supervisors require the prior approval of policy conditions and insurance premiums, but do not conduct risk-based capital regulation. This paper compares the outcome of insurance rate regulation and riskbased capital requirements by deriving stock insurers’ best responses. It turns out that binding price floors affect insurers’ optimal capital structures and induce them to choose higher safety levels. Risk-based capital requirements are a more efficient instrument of solvency regulation and allow for lower insurance premiums, but may come at the cost of investment efforts into adequate risk monitoring systems. The paper derives threshold values for regulator’s investments into risk-based capital regulation and provides starting points for designing a welfare-enhancing insurance regulation scheme.