Should the monetary policy rule be different in a financial crisis?

This article reviews the finding that standard loss functions in output and inflation are higher during discretionary periods than in periods during which monetary policy is described by a rule, such as the Taylor rule. It shows that the finding is consistent with earlier research, but argues that we really do not know if the Taylor rule would have improved performance during the recent financial crisis. The article then considers modifications of policy rules to deal with changes in interest rate spreads, credit aggregates and banks׳ balance sheets.     

On uniform convergence of undiscounted optimal programs in the Mitra–Wan forestry model: The strictly concave case

In this paper, we show that the 1986 Mitra–Wan result establishing asymptotic convergence of maximal programs to the unique golden-rule forest in the case of undiscounted, strictly concave felicity functions can be strengthened, in the same setting, to the  uniform  asymptotic convergence of  optimal  programs to the unique golden-rule forest. We work with a notationally reformulated version of the model that may have independent interest.     

浅谈建筑设计中的艺术形式感

建筑作为一种实用艺术,不仅要体现出适用的特点,而且要有美感,要满足人们精神感受上的审美要求。建筑作为艺术门类的一种,遵循和谐和多样统一的美学基本原则。作为一名建筑师来说,创造符合功能的形式美建筑是不可忽视的。     

The evolution of U.S. monetary policy: 2000–2007

A vector autoregression with time-varying parameters is used to characterize changes in Federal Reserve policy that occurred from 2000 through 2007 and describe how they affected the performance of the U.S. economy. Declining coefficients in the model׳s estimated policy rule point to a shift in the Fed׳s emphasis away from stabilizing inflation over this period. More importantly, however, the Fed held the federal funds rate persistently below the values prescribed by this rule. Under this more discretionary policy, inflation overshot its target and the funds rate followed a path reminiscent of the “stop-go” pattern that characterized Fed behavior prior to 1979.     

Making Good Decisions with Minimal Information: Simultaneous and Sequential Choice

The adaptive pressures facing humans and other animals to make decisions quickly can be met both by increasing internal information-processing speed and by minimizing the amount of information to be used. Here we focus on the latter effect and ask how, and how well, agents can make good decisions with a minimal amount of information, using two specific tasks as examples. When a choice must be made between simultaneously-available options, minimal information in the form of binary recognition (whether or not each item is recognized) can be used in the recognition heuristic to choose effectively. When options are encountered sequentially one at a time, minimal information as to whether or not each option is the best encountered so far is sufficient to guide agents using a simple search-cutoff rule to high performance along several choice criteria. Both of these examples have important economic as well as biological applications, and show the power of simple fast and frugal heuristics to produce good decisions with little information. This revised version was published online in August 2006 with corrections to the Cover Date.     

On the efficiency of the negligence rule

The three versions of the negligence rule discussed in the literature differ regarding whether a negligent injurer is liable for the entire loss or only for the incremental loss; or regarding whether negligence is defined as failure to take at least due care or failure to take a cost‐justified precaution. It is shown in the paper that the incremental version with untaken precaution notion of negligence is not efficient; not even for the unilateral case. The paper also establishes, for the bilateral case, the efficiency of the incremental version with the shortfall‐from‐due‐care way of defining negligence.     

论吉利斯的长趋势性向解释

吉利斯的长趋势性向解释从批判频率解释的操作主义入手，以自然科学中关于概念更新的非操作主义理论为基础。为了使概率恰好地与频率相联系，吉利斯提出了概率陈述的可证伪规则，并运用这个规则推导出概率的统计频率稳定性定律和排斥赌博规律定律。     

Empirical tests of real estate market efficiency

Recent empirical research using real estate data has supported the weak and semi-strong forms of the efficient markets hypothesis. Previous studies have not included an estimate of expected appreciation into the tests of market efficiency, thus raising a question about the reliability of the results. We first use a market model to test for market efficiency with results similar to those reported by others. We next use a dynamic multiple indicator, multiple cause (DYMIMIC) model, which extracts a vector of expected appreciation from the price data, to test market efficiency. This approach produces superior results and a stronger conclusion about the efficiency of housing markets. The results indicate limited adjustment delays which can be explained by the existence of high transactions and search costs.