قوانین سیاست های پولی، قیمت دارایی ها و یادگیری انطباقی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|27916||2013||8 صفحه PDF||سفارش دهید||6150 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Financial Stability, Volume 9, Issue 3, September 2013, Pages 251–258
Following the damaging real effects of asset price fluctuations over the recent financial crisis, the debate on the appropriate role of such prices in a monetary policy context has gained renewed attention. This paper argues that a direct monetary policy response to asset prices is not desirable under common instrumental rate rules. To illustrate this point, we build an adaptive learning model, that extends existing learning models in monetary policy, most notably, Bullard and Mitra (2002). The result remains valid in a context with heterogeneous beliefs and is robust to an optimal monetary policy rule including a weight on asset prices.
The issue of what role asset prices should play in monetary policy has gained renewed momentum in the aftermath of the recent financial crisis, and this issue remains far from resolved. After a first wave of contributions to this debate in the early 90s, primarily following the conflicting views of Bernanke and Gertler (2001) and Cecchetti et al. (2000), there has been resurgent interest among both policymakers and academic researchers.1 Although, as Bernanke (2007) stated, many interesting issues in contemporary monetary theory require an analytical framework that involves learning, the question of how monetary policy should respond to asset price developments has rarely been approached using a framework of adaptive learning.2 In fact, although expectations play a vital role in modern monetary policy settings, a disproportionately large part of the related literature continues to rely on the rational expectations hypothesis. This paper shows that a direct monetary policy response to asset prices is not desirable under common interest rate rules. We illustrate this point with three strategies. First, an adaptive learning model is presented that extends the seminal work of Bullard and Mitra (2002) by adding a response to asset prices in the policy rule and generalizing their chief result with regard to the Taylor principle. Building on the work by Carlstrom and Fuerst (2007), an interest rate rule responding to expectations is added, and E-Stability conditions are assessed. A few authors have approached some type of reaction to asset prices using adaptive learning, most notably Pfajfar and Santoro (2012) and Assenza et al. (2011). Diverging from these papers, we focus on a standard new Keynesian macroeconomic model of monetary policy transmission instead of allowing for cost-channel effects.3 Second, we show that the result is robust to heterogeneity in agents’ beliefs using a framework similar to that of Guse (2005), who argues that stability results may differ considerably from the homogeneous case. The introduction of heterogeneity in the formation of expectations is a natural step, as the evidence both on inflation expectation surveys and asset price expectations appears to weaken the representative agent hypothesis.4 Finally, the paper derives the optimal monetary policy allowing for asset prices, extending the expectations-based rule proposed by Evans and Honkapohja (2003a). The remainder of this paper is organized as follows. The next section briefly describes the small macroeconomic model of households and firms. Section 3 presents the benchmark learning environment with homogeneous expectations and instrumental rules. In Sections 4 and 5, we allow for heterogeneous beliefs and optimal monetary policy, and Section 6 concludes.
نتیجه گیری انگلیسی
This paper shows that the response to asset prices is not desirable from a monetary policy perspective. For this purpose, we build a model to assess the conditions for determinacy and stability under learning of an extended monetary policy rule that considers asset price variations. The model builds on those of Bullard and Mitra (2002) and Carlstrom and Fuerst (2007) by simultaneously considering E-Stability in a learning environment and a forward expectations policy rule with an additional role of asset prices. The mechanism behind the paper's main finding is the following. The negative relationship between firm profits (and consequently dividends and asset prices) and marginal costs means that as inflation rises, so do marginal costs, leading asset prices to tend to fall. A response of the policy rate to asset prices in the same direction undermines the CB's response to inflation, leading to the indeterminacy of REE. We found that this effect also threatens E-Stability, as we have shown using both a contemporaneous and a forward expectations interest rate rule. Considering heterogeneous beliefs leads to a similar outcome. More precisely, if there is a considerable fraction of agents in the economy who form expectations examining past values of key variables (in our case, asset price developments, inflation and the output gap), non-fundamental equilibria that are not learnable may arise. Meanwhile, the main result also applies to optimal monetary policy analysis, at least when an expectations-based monetary policy rule in the sense of Evans and Honkapohja, 2003a and Evans and Honkapohja, 2003b is considered. Given that stock price booms and busts have caused considerable damage to the financial stability of many industrialized countries in recent years, and because no clear-cut stance of monetary policy is to be advised, further measures may also be considered. Indeed, some authors and policymakers have recently mentioned macroprudential regulation as an alternative to cope with financial imbalances and the possibility of booms and busts (see IMF (2011)). Less discussed are the potential negative side effects of increased regulation. Further research may also extend the ideas of heterogeneity in various ways. Agents may be allowed to switch between beliefs, depending on some measure of past performance of their forecast, as in Guse (2005), or Branch and Evans (2011). Alternatively, some agents may also form rational expectations, whereas others behave adaptively, as in Branch and McGough (2009).