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※ 번역할 언어 선택

Governor Frederic S. Mishkin
At the Federal Reserve Bank of New York, New York, New York
January 11, 2008

Monetary Policy Flexibility, Risk Management, and Financial Disruptions

In my remarks today, I would like to consider the rationale for greater flexibility in monetary policy during periods of financial disruptions. Before doing so, however, I would like to make not just one, but two important disclaimers. First, as usual, my remarks reflect only my own views and are not intended to reflect those of the Federal Open Market Committee (FOMC) or of anyone else associated with the Federal Reserve System. And second, my comments today should not be viewed as suggesting what policy actions I would be likely to advocate at the next FOMC meeting; rather, my purpose here is to discuss at a general level what can be said about the appropriate framework for monetary policy when we face a financial disruption of the sort that we have seen recently.

I have two reasons for making the second disclaimer. First, in some circumstances, the appropriate near-term path for policy rates can be highly uncertain and may well evolve right up until the time of the meeting, depending on the implications of the incoming data. Second, >as I noted in a speech in late November, I think there is too much focus on what decision will be made about the federal funds rate target at the next FOMC meeting (Mishkin, 2007e). What is important for pricing most financial assets is the path of monetary policy, not the particular action taken at a single meeting. For these reasons, I hope the recent enhancements to the Federal Reserve’s communication strategy--especially the greater prominence of the macroeconomic projections of FOMC participants--will help shift attention toward our medium-term objectives and our approach in meeting these objectives.1

In particular, the Congress has given the Federal Reserve a specific mandate (often referred to as the dual mandate) of fostering the objectives of price stability and maximum employment. Therefore, when the economy faces a disruption in financial markets, monetary policy must aim at balancing the risks to both economic growth and inflation. In the remainder of this speech, I will elaborate a bit further about why financial market disruptions can pose significant risks to the macroeconomy. Then I will explain how the science of monetary policy can help provide a conceptual framework for a systematic approach to managing these risks, and I will briefly discuss how that framework can be useful for understanding the course of Federal Reserve policy over the past few months.

Financial Disruptions and Macroeconomic Risk
Before considering the appropriate policy response to strains in financial markets, it is essential to consider the sources of these strains and the potential consequences for the macroeconomy. In general, the U.S. financial system is an efficient mechanism for channeling funds to individuals or corporations with worthy investment opportunities, because the financial markets are highly competitive and provide strong incentives for collecting and processing information.

Although financial markets and institutions deal with large volumes of information, some of this information is by nature asymmetric; that is, one party to a financial contract (typically the lender) has less accurate information about the likely distribution of outcomes than does the other party (typically the borrower).2 Historically, banks and other financial intermediaries have played a major role in reducing the asymmetry of information, partly because these firms tend to have long-term relationships with their clients. Recent years have witnessed the development of new types of financial institutions and of new markets for trading financial products, and these innovations have had the potential (not always realized) to contribute to the efficient flow of information.

The continuity of this information flow is crucial to the process of price discovery--that is, the ability of market participants to assess the fundamental worth of each financial asset. During periods of financial distress, however, information flows may be disrupted and price discovery may be impaired. As a result, such episodes tend to generate greater uncertainty, which contributes to higher credit spreads and greater reluctance to engage in market transactions.

As I noted in another recent speech, financial disruptions are associated with two distinct types of risk: valuation risk and macroeconomic risk (Mishkin, 2007d). Valuation risk refers to the extent that market participants become more uncertain about the returns on a specific asset, especially in cases where the security is highly complex and its underlying creditworthiness is relatively opaque. In recent months, for example, this type of risk has been central to the repricing of many structured credit products, as investors have struggled to understand how potential losses in subprime mortgages might filter through the various layers of securities linked to these loans.

While valuation risk is relevant for individual investors, monetary policymakers are concerned with macroeconomic risk. In particular, strains in financial markets can spill over to the broader economy and have adverse consequences on output and employment. Furthermore, an economic downturn tends to generate even greater uncertainty about asset values, which could initiate an adverse feedback loop in which the financial disruption restrains economic activity; such a situation could lead to greater uncertainty and increased financial disruption, causing a further deterioration in macroeconomic activity, and so on. In the academic literature, this phenomenon is generally referred to as the financial accelerator (Bernanke and Gertler, 1989; Bernanke, Gertler, and Gilchrist, 1996, 1999).

The quality of balance sheets of households and firms comprise a key element of the financial accelerator mechanism, because some of the assets of each borrower may serve as collateral for its liabilities. The use of collateral helps mitigate the problem of asymmetric information, because the borrower’s incentive not to engage in excessive risk-taking is strengthened by the threat of losing the collateral: If a default does occur, the lender can take title to the borrower’s collateral and thereby recover some or all of the value of the loan. However, a macroeconomic downturn tends to diminish the value of many forms of collateral, thereby exacerbating the impact of frictions in credit markets and reinforcing the propagation of the adverse feedback loop.

Risk Management and the Science of Monetary Policy
Given that a financial market disruption can pose significant risks to the macroeconomy, risk management is crucial in formulating the appropriate response of monetary policy. Unfortunately, most existing studies of optimal monetary policy have completely abstracted from considerations of macroeconomic risk, because these studies use specific formulations or approximations which imply that the design of the optimal monetary policy does not depend on the magnitude or direction of uncertainty facing the economy--an implication referred to as certainty equivalence.

To elaborate on these issues, it’s necessary for me to proceed at a somewhat more technical level, but I promise to use plain English again later in the speech. In particular, the standard textbook approach to analyzing optimal monetary policy utilizes a linear-quadratic (LQ) framework, in which the equations describing the dynamic behavior of the economy are linear and the objective function specifying the goals of policy is quadratic. For example, in light of the dual mandate, monetary policy is often characterized as seeking to minimize a loss function comprising the squared value of the inflation gap (that is, actual inflation minus desired inflation) and the squared value of the output gap (that is, actual output minus potential output).

Under these assumptions, the optimal policy is certainty equivalent: This policy can be characterized by a linear time-invariant response to each shock, and the magnitude of these responses does not depend on the variances or any other aspect of the probability distribution of the shocks. In such an environment, optimal monetary policy does not focus on risk management. Furthermore, when financial market participants and wage and price setters are relatively forward-looking, the optimal policy under commitment is characterized by considerable inertia.3

Indeed, the actual course of monetary policy over the past quarter-century has typically been very smooth in the United States as well as in many other industrial economies.
For example, the Federal Reserve has usually adjusted the federal funds rate in increments of 25 or 50 basis points (that is, 1/4 or 1/2 percentage point) and sharp reversals in the funds rate path have been rare. Numerous empirical studies have characterized monetary policy using Taylor-style rules in which the policy rate responds to the inflation gap and the output gap; these studies have generally found that the fit of the regression equation is improved by including a lagged interest rate that reflects the smoothness of the typical adjustment pattern.4

While an LQ framework may provide a reasonable approximation to how monetary policy should operate under fairly normal circumstances, this approach is less likely to be adequate for thinking about monetary policy when the risk of poor economic performance is unusually high. First, the dynamic behavior of the economy may well exhibit nonlinearities, at least in response to some shocks (Hamilton, 1989; Kim and Nelson, 1999; and Kim, Morley, and Piger, 2005). Furthermore, the use of a quadratic objective function does not reflect the extent to which most individuals have strong preferences for minimizing the incidence of worst-case scenarios. Therefore, given that the central bank’s ultimate goal should be to maximize the public welfare, I believe that the design of monetary policy ought to reflect the public’s preferences, especially with respect to avoiding particularly adverse economic outcomes.

Most of the quantitative studies of optimal monetary policy have also assumed that the shocks hitting the economy have a time-invariant Gaussian distribution, that is, a classical bell curve with symmetric and well-behaved tails. In reality, however, the distribution of shocks hitting the economy is more complex. In some instances, the uncertainty facing the economy is clearly skewed in one direction or another; again, this is likely when there are significant financial disruptions. The Federal Reserve often reports on our judgments regarding the degree of skewness and the associated economic costs by giving assessments of the “Balance of Risks” in the press releases that are issued following FOMC meetings.

In addition, at least in some circumstances, the shocks hitting the economy may exhibit excess kurtosis, commonly referred to as tail risk because the probability of relatively large disturbances is higher than would be implied by a Gaussian distribution. In that light, one element of the recent enhancements to the Federal Reserve’s communication strategy is that FOMC participants now provide assessments of the relative degree of uncertainty. For example, in the “Summary of Economic Projections”issued in late November, FOMC participants indicated that the degree of uncertainty regarding the economic growth outlook was relatively high compared to the average degree of uncertainty over the past two decades. This account could be interpreted as a statement that the Committee perceived the tail risk as unusually large.

With a nonquadratic objective function (consistent with the importance of uncertainty for the course of monetary policy) as well as nonlinear dynamics and non-Gaussian shocks, optimal monetary policy will also be nonlinear and will tend to focus on risk management. Policy in this setting tends to respond aggressively when a large shock becomes evident; for this reason, the degree of inertia in such cases may be markedly lower than in more routine circumstances. Indeed, as I will argue, I believe that financial disruptions of the sort that have been experienced in recent months tend to have highly nonlinear effects on the economy. Thus, compared with the standard case, optimal policy may well involve much more rapid adjustment--a pattern that I will refer to as policy flexibility.

Formal models of how monetary policy should respond to financial disruptions are unfortunately not yet available, and this is an area of research that I plan to pursue with Board staff. However, I do have some thoughts about what a systematic framework should look like, and I would like to share them with you without going into any further technical details.

A Risk-Management Framework for Dealing with Financial Disruptions
Although the assumptions behind the LQ framework might be reasonable during normal times, financial disruptions are likely to produce large deviations from these assumptions, making it especially important to adopt a more flexible framework for analyzing the behavior of a central bank that practices risk management. What factors come into play with special vigor during financial disruptions? First, financial disruptions are likely to lead to highly nonlinear behavior because the cost and availability of credit can shift suddenly. Furthermore, even though linear approximations of the financial accelerator mechanism have typically been used in recent quantitative studies, this mechanism is, in fact, highly nonlinear (Levin, Natalucci, and Zakrajšek, 2004). Finally, because financial disruptions, if severe enough, raise the probability of particularly adverse outcomes, the standard approach of employing a quadratic approximation of the objective function may not be sufficiently accurate to convey the extent to which policymakers seek to avoid such outcomes in maximizing the public’s welfare.

In light of these risk-management considerations, how should monetary policy respond to financial disruptions?

Periods of financial instability are characterized by valuation risk and macroeconomic risk. Monetary policy cannot--and should not--aim at minimizing valuation risk, but policy should aim at reducing macroeconomic risk. By cutting interest rates to offset the negative effects of financial turmoil on aggregate economic activity, monetary policy can reduce the likelihood that a financial disruption might set off an adverse feedback loop. The resulting reduction in uncertainty can then make it easier for the markets to collect the information that facilitates price discovery, thus hastening the return of normal market functioning.

To achieve this result most effectively, monetary policy needs to be timely, decisive, and flexible. First, timely action is crucial when an episode of financial instability becomes sufficiently severe to threaten the core macroeconomic objectives of the central bank. In such circumstances, waiting too long to ease policy could result in further deterioration of the macroeconomy and might well increase the overall amount of easing that would eventually be needed. Therefore, monetary policy must be at least as preemptive in responding to financial shocks as in responding to other types of disturbances to the economy. When financial markets are working well, monetary policy can respond primarily to the incoming flow of economic data about production, employment, and inflation. When a financial disruption occurs, however, greater consideration needs to be given to indicators of market liquidity, credit spreads, and other financial market measures that can provide information about sharp changes in the magnitude of tail risk to the macroeconomy.

Second, policymakers should be prepared for decisive action in response to financial disruptions. In such circumstances, the most likely outcome--referred to as the modal forecast--for the economy may be fairly benign, but there may be a significant risk of more severe adverse outcomes. In such circumstances, the central bank may prefer to take out insurance by easing the stance of policy further than if the distribution of probable outcomes were perceived as fairly symmetric around the modal forecast. Moreover, in such circumstances, these policy actions should not be interpreted by the public or market participants as implying a deterioration in the central bank’s assessment of the most likely outcome for the economy, but rather as an appropriate form of risk management that reduces the risk of particularly adverse outcomes.

Third, policy flexibility is crucial throughout the evolution of a financial market disruption. During the onset of the episode, this flexibility may be evident from the decisive easing of policy that is intended to forestall the contractionary effects of the disruption and provide insurance against the downside risks to the macroeconomy. However, it is important to recognize that financial markets can also turn around quickly, thereby reducing the drag on the economy as well as the degree of tail risk. Therefore, the central bank needs to monitor credit spreads and other incoming data for signs of financial market recovery and, if necessary, take back some of the insurance; thus, at each stage of the episode, the appropriate monetary policy may exhibit much less smoothing than would be typical in other circumstances.

Of course, while policymakers may need to react aggressively to financial market information that indicates a significant shift in macroeconomic risks, monetary policy would typically move back toward a more incremental approach once the risks to the macroeconomy have returned to more usual levels.

Risk Management and the Anchoring of Inflation Expectations
An important proviso to my discussion thus far involves the other part of the dual mandate, price stability. A central bank must always be concerned with inflation as well as growth. As I have emphasized in an earlier speech about inflation dynamics, the behavior of inflation is significantly influenced by the public’s expectations about where inflation is likely to head in the long run (Mishkin, 2007a). Therefore, preemptive actions of the sort I have described here would be counterproductive if these actions caused an increase in inflation expectations and the underlying rate of inflation; in other words, the flexibility to act preemptively against a financial disruption presumes that inflation expectations are well anchored and unlikely to rise during a period of temporary monetary easing. Indeed, as I have argued elsewhere, a commitment to a strong nominal anchor is crucial for both aspects of the dual mandate, that is, for achieving maximum employment as well as for keeping inflation under control (Mishkin, 2007b).

How can a central bank keep inflation expectations solidly anchored so it can respond preemptively to financial disruptions? The central bank has to have earned credibility with financial markets and the public through a record of previous actions to maintain low and stable inflation. Furthermore, the central bank needs to clearly indicate the rationale for its policy actions. Policymakers also need to monitor information about underlying inflation and longer-run inflation expectations, and if the evidence indicates that these inflation expectations have begun rising significantly, the central bank should be prepared to hold steady or even raise the policy rate.

The Federal Reserve’s Recent Monetary Policy Decisions
The framework I have outlined here can be useful in understanding the rationale for the recent decisions of the Federal Reserve and our policy approach going forward. Yesterday, Chairman Bernanke provided a detailed discussion of economic and financial developments and of the Federal Reserve’s policy strategy, so here I will just relate some key points of his discussion to the major themes that I have emphasized today.

First, we are proceeding in a timely manner in countering any developments that might threaten economic or financial stability. The FOMC has not been basing its decisions solely on the incoming flow of economic data; for example, the sequence of interest rate cuts was initiated last fall even though growth in the gross domestic product had been quite strong in the third quarter. Rather, our policy approach has reflected the rapid deterioration of financial market conditions, which has contributed to a worsening of the economic outlook and the emergence of pronounced downside risks to economic growth and employment.

Second, in my view, the Federal Reserve has been acting and will continue to act decisively, in the sense that our policy strategy reflects the evolution of the balance of risks and not simply a change in the modal outlook for the macroeconomy. The disruption in financial markets poses a substantial downside risk to the outlook for economic growth, and adverse economic or financial news has the potential to cause further strains. In that light, the Federal Reserve’s policy strategy is aimed at providing insurance to help avoid more severe macroeconomic outcomes.

Third, because we recognize that financial and economic conditions can change quickly, the Federal Reserve is prepared to respond flexibly to incoming information. Of course, in making its decisions, the Federal Reserve also gives careful consideration to the outlook and risks associated with the second aspect of our dual mandate, namely, price stability. Because longer-run inflation expectations appear to have remained reasonably well anchored, in my view, the easing of the stance of policy in response to deteriorating financial conditions seems unlikely to have an adverse impact on the outlook for inflation. Nonetheless, we will continue to monitor incoming data on inflation and inflation expectations, especially given the potential risks to price stability that are associated with the rapid increase in energy prices and the depreciation of the dollar. In short, the FOMC will determine the future course of monetary policy in light of the evolution of the macroeconomic outlook and the balance of risks to our objectives of maximum employment and price stability.

Conclusions
The monetary policy that is appropriate during an episode of financial market disruption is likely to be quite different than in times of normal market functioning. When financial markets experience a significant disruption, a systematic approach to risk management requires policymakers to be preemptive in responding to the macroeconomic implications of incoming financial market information, and decisive actions may be required to reduce the likelihood of an adverse feedback loop. The central bank also needs to exhibit flexibility--that is, less inertia than would otherwise be typical--not only in moving decisively to reduce downside risks arising from a financial market disruption, but also in being prepared to take back some of that insurance in response to a recovery in financial markets or an upward shift in inflation risks.

Finally, while I have argued that monetary policy needs to be decisive and timely in responding to a financial market disruption, a lot of art as well as science is involved in determining the severity and duration of the disruption and the associated implications for the macroeconomy (Mishkin, 2007c). Indeed, assessing the macroeconomic risks to output and inflation in such circumstances remains among the most difficult challenges faced by monetary policymakers. Furthermore, a central bank may well be able to employ non-monetary tools--such as liquidity provision--to help alleviate the adverse impact from financial disruptions. All of these considerations must be taken into account in determining the most appropriate course of monetary policy.


References
Benigno, Pierpaolo, and Michael Woodford (2003). “Optimal Monetary and Fiscal Policy: A Linear-Quadratic Approach,” in Mark Gertler and Kenneth Rogoff, eds., NBER Macroeconomics Annual 2003. Cambridge, Mass.: MIT Press, pp. 271-332.

Bernanke, Ben S. (2004). “Gradualism,” speech delivered at an economics luncheon co-sponsored by the Federal Reserve Bank of San Francisco (Seattle Branch) and the
University of Washington, held in Seattle, May 20.

Bernanke, Ben S., and Mark Gertler (1989). “Agency Costs, Net Worth, and Business Fluctuations,” Leaving the Board American Economic Review, vol. 79 (March), pp. 14-31.

Bernanke, Ben S., Mark Gertler, and Simon Gilchrist (1996). “The Financial Accelerator and the Flight to Quality,” Leaving the Board Review of Economics and Statistics, vol. 78 (February), pp. 1-15.

Bernanke, Ben S., Mark Gertler, and Simon Gilchrist (1999). “The Financial Accelerator in a Quantitative Business Cycle Framework,” in John B. Taylor and Michael Woodford, eds., Handbook of Macroeconomics, vol. 1, part 3. Amsterdam: North-Holland, pp. 1341-93.

Clarida, Richard, Jordi Galí, and Mark Gertler (1998). “Monetary Policy Rules in Practice: Some International Evidence,” Leaving the Board European Economic Review, vol. 42 (June), pp. 1033-67.

Clarida, Richard, Jordi Galí, and Mark Gertler (1999). “The Science of Monetary Policy: A New Keynesian Perspective,” Leaving the Board Journal of Economic Literature, vol. 37 (December), pp. 1661-707.

Clarida, Richard, Jordi Galí, and Mark Gertler (2000). “Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory,” Leaving the Board Quarterly Journal of Economics, vol. 115 (February), pp. 147-80.

English, William B., William R. Nelson, and Brian P. Sack (2003). “Interpreting the Significance of the Lagged Interest Rate in Estimated Monetary Policy Rules,” Leaving the Board Contributions to Macroeconomics, vol. 3 (no. 1), article 5.

Erceg, Christopher J., Dale W. Henderson, and Andrew T. Levin (2000). “Optimal Monetary Policy with Staggered Wage and Price Contracts,” Leaving the Board Journal of Monetary Economics, vol. 46 (October), pp. 281-313.

Giannoni, Marc P. , and Michael Woodford (2005). “Optimal Inflation-Targeting Rules,” in Ben S. Bernanke and Michael Woodford, eds., Inflation Targeting. Chicago: University of Chicago Press, pp. 93-172.

Goodfriend, Marvin, and Robert King (1997). “The New Neoclassical Synthesis and the Role of Monetary Policy,” in Ben S. Bernanke and Julio J. Rotemberg, eds., NBER Macroeconomics Annual 1997. Cambridge, Mass.: MIT Press, pp. 231-83.

Hamilton, James D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle,” Leaving the Board Econometrica, vol. 57 (March), pp. 357-84.

Kim, Chang-Jin, and Charles Nelson (1999). “Has the U.S. Economy Become More Stable? A Bayesian Approach Based on a Markov-Switching Model of the Business Cycle,” Review of Economics and Statistics, vol. 81 (November), pp. 608-16.

Kim, Chang-Jin, James Morley, and Jeremy Piger (2005). “Nonlinearity and the Permanent Effects of Recessions,” Leaving the Board Journal of Applied Econometrics, vol. 20 (no. 2), pp. 291-309.

King, Robert G., and Alexander L. Wolman (1999). “What Should the Monetary Authority Do When Prices Are Sticky?” in John Taylor, ed., Monetary Policy Rules. Chicago: University of Chicago Press, pp. 349-98.

Levin, Andrew T., Fabio M. Natalucci, and Egon Zakrajšek (2004). “The Magnitude and Cyclical Behavior of Financial Market Frictions,” Finance and Economics Discussion Series 2004-70. Washington: Board of Governors of the Federal Reserve System, December.

Levin, Andrew, Alexei Onatski, John C. Williams, and Noah Williams (2005). “Monetary Policy under Uncertainty in Micro-Founded Macroeconometric Models,” in Mark Gertler and Kenneth Rogoff, eds., NBER Macroeconomics Annual 2005. Cambridge, Mass.: MIT Press, pp. 229-88.

Mishkin, Frederic S. (2007a). “Inflation Dynamics,” speech delivered at the Annual Macro Conference, Federal Reserve Bank of San Francisco, San Francisco, March 23.

Mishkin, Frederic S. (2007b). “Monetary Policy and the Dual Mandate,” speech delivered at Bridgewater College, Bridgewater, Va., April 10.

Mishkin, Frederic S. (2007c). “Will Monetary Policy Become More of a Science?” Finance and Economics Discussion Series 2007-44. Washington: Board of Governors of the Federal Reserve System, September.

Mishkin, Frederic S. (2007d). “Financial Instability and Monetary Policy,” speech delivered at the Risk USA 2007 Conference, New York, November 5.

Mishkin, Frederic S. (2007e). “The Federal Reserve’s Enhanced Communication Strategy and the Science of Monetary Policy,” speech delivered to the Undergraduate Economics Association, Massachusetts Institute of Technology, Cambridge, Mass., November 29.

Rotemberg, Julio, and Michael Woodford (1997). “An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy,” in Ben S. Bernanke and Julio J. Rotemberg, eds., NBER Macroeconomics Annual 1997. Cambridge, Mass.: MIT Press, pp. 297-346.

Sack, Brian (2000). “Does the Fed Act Gradually? A VAR Analysis,” Leaving the Board Journal of Monetary Economics, vol. 46 (August), pp. 229-56.

Schmitt-Grohé, Stephanie, and Martin Uribe (2005). “Optimal Fiscal and Monetary Policy in a Medium-Scale Macroeconomic Model,” in Mark Gertler and Kenneth Rogoff, eds., NBER Macroeconomics Annual 2005. Cambridge, Mass.: MIT Press, pp. 383-425.

Smets, Frank, and Raf Wouters (2003). “An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area,” Leaving the Board Journal of the European Economic Association, vol. 1 (September), pp. 1123-75.

Woodford, Michael (2003). Interest and Prices: Foundations of a Theory of Monetary Policy. Princeton: Princeton University Press.

Footnotes

1. I appreciate the comments and assistance of William English, Andrew Levin, Brian Madigan, Roberto Perli, David Reifschneider, and David Wilcox.

2. Such asymmetry leads to two prominent difficulties for the functioning of the financial system: adverse selection and moral hazard. Adverse selection arises when investments that are most likely to produce an undesirable (adverse) outcome are the most likely to be financed (selected). For example, investors who intend to take on large amounts of risk are the most likely to be willing to seek out loans because they know that they are unlikely to pay them back. Moral hazard arises because a borrower has incentives to invest in high-risk projects, in which the borrower does well if the project succeeds but the lender bears a substantial loss if the project fails.

3. The now-classic textbook on this topic is Woodford (2003); refer also to Goodfriend and King (1997); Rotemberg and Woodford (1997); Clarida, Gali, and Gertler (1999); King and Wolman (1999); Erceg, Henderson, and Levin (2000); Benigno and Woodford (2003); Giannoni and Woodford (2005); Levin and others (2005); and Schmitt-Grohé and Uribe (2005);

4. Clarida, Gali, and Gertler (1998, 2000); Sack (2000); English, Nelson, and Sack (2003); Smets and Wouters (2003); Levin and others (2005); further discussion is in Bernanke (2004).

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용산·태릉·과천 등 6만호 조성 [서울=뉴스핌] 이동훈 선임기자 = 서울 용산국제업무지구와 태릉CC(골프장), 경기 과천 경마장(렛츠런파크서울)을 비롯한 서울 도심부와 경기 서울 근교지역에 총 6만가구가 공급된다. 이를 위해 11개 도심 내 공공부지에 4만3500가구가 공급되며 신규 공공주택지구를 새로 지정해 6300가구를 짓는다. 또 도심 내 노후청사를 활용해 모두 9900가구가 지어질 예정이다. 오는 2027년부터 2030년까지 순차적으로 착공한다. ◆ '9·7 주택공급 확대방안' 후속초지...도심 6만 가구 조성 29일 국토교통부에 따르면 정부는 이같은 내용을 담은 '도심 주택공급 확대 및 신속화 방안'을 발표했다.  '9·7 주택공급 확대방안'의 후속조치인 이번 1·29 대책에서는 도심권에서 6만가구가 공급된다. 지역별로 서울은 3만2000가구(53.3%), 경기 2만8000가구(46.5%), 인천 100가구(0.2%)가 각각 배정됐다.  공급 계획 [자료=국토부] 먼저 도심내 공공부지에는 4만3500가구를 짓는다. 이 가운데 서울시와 정부가 마련한 기존 공급물량 7400가구를 제외하면 3만6100가구가 새로 지정된 물량이다.  서울 용산구 용산국제업무지구와 캠프킴에서 기존계획 물량 7400가구를 포함한 총 1만2600가구가 공급된다. 서울시가 주관하는 용산국제업무지구에서는 6000가구의 주택을 공급할 예정이었으나 이번 정부 방침에 따라 주택공급수가 1만가구로 4000가구 늘어나게 됐다. 서울시가 주택공급 확대에 대한 문제로 지적했던 학교 신설은 중단한다. 착공은 2028년으로 예정됐다. 수도권전철 남영역 인근 캠프킴 부지의 주택규모는 2500가구로 기존 1400가구에서 1100가구 더 확대됐다. 2029년 착공을 추진한다. 아울러 인기 주거지역인 서빙고동 '501 정보대'부지에도 신혼부부 등을 위한 소형주택 150가구를 짓는다. 2029년 착공 예정이다.  경기 과천시 일원 과천경마장과 방첩사 부지에서 9800가구를 건립한다. 정부는 과천 경마장(115만㎡)과 국군방첩사령부(28만㎡) 이전 후 해당 부지 총 143만㎡를 통합 개발한다는 방침이다. 경마장과 방첩사 이전계획을 국방부와 농식품부와 협의해 올 상반기내 완료하고 오는 2030년 착공할 예정이다.  문재인 정부시절 주택공급 후보지로 떠올랐던 서울 노원구 태릉CC 총 87만5000㎡에는 6800가구가 공급된다. 정부는 장기간 진척되지 못하던 태릉CC 개발사업을 국가유산청과의 협의를 거쳐 본격 추진하고 주민을 위한 교통대책과 충분한 녹지공간 마련에 나선다는 방침이다. 세계유산영향평가를 거친 후 공공주택 지구지정과 지구계획 수립 등을 병행해 2030년 착공을 추진한다.  경기 성남시 판교테크노밸리 및 성남시청과 인접한 곳에 신규 공공주택지구 성남금토2지구와 성남여수2지구 약 67.4만㎡(20만평)를 지정한다. 이들 신규 택지에는 6300가구가 공급될 예정이다. 두 공공택지는 인허가 및 보상을 완료한 후 착공은 2030년 목표다.  서울 동대문구 일원에서는 국방연구원과 인접한 한국경제발전전시관을 함께 이전하고 이전 부지 총 5만5000㎡ 규모에 주택 1500가구를 짓는다. 국토부는 국조실·기후부·성평등부와 협의해 해당 기관을 2027년 상반기까지 이전하고 이전 시점에 맞춰 사업 승인, 토지 매입 등을 추진해 2029년 착공한다는 방침이다.   서울 인접 역세권 부지와 그간 장기 지연된 사업의 계획을 변경해 총 1만1500여가구를 신규 공급한다. 정부는 이들 지구에 대해 예비 타당성 조사를 면제함으로써 사업 속도를 높일 계획이다.  먼저 경기 광명시 광명경찰서 부지 약 9000㎡에 550가구를 짓는다. 2027년까지 경찰서 이전을 완료하고 이전 일정에 맞춰 2029년 착공한다. 경기 하남시 신장 테니스장 부지 약 5000㎡에는 300가구가 공급된다. 2029년 착공을 목표로 한다.  서울 강서구 강서 군부지 약 7만㎡에는 918가구가 건립된다. 당초 부지 매각 방식으로 추진됐던 이 사업은 위탁개발 방식으로 변경해 재개된다. 2027년 착공될 예정이다. 서울 금천구 독산동 공군부대 13만㎡부지는 군부대 압축·고밀개발 방식으로 2900가구를 공급한다. 착공은 2030년이다.  경기 남양주시 퇴계원 일대 군부대 부지 35만㎡에 4180가구를 짓는다. 예비 타당성 조사를 면제해 2029년 착공을 추진한다. 또 경기 고양시 구국방대학교 부지 33만㎡에는 2570가구를 공급한다. 2029년 착공을 목표로 서울 상암DMC와 잇는 직주근접 미디어밸리를 조성할 방침이다. ◆ 공급확대에 범부처 역량 결집...투기 방지도 병행 정부는 이번 1·29 '도심 주택공급 확대 및 신속화 방안'의 원활한 추진을 위해 '주택공급촉진 관계장관회의'를 신설한다. 회의에서는 발표 부지에 대한 이행 일정 점검 및 조기화를 추진하고 신규 물량 발굴에도 지속 노력한다는 방침이다. 특히 기존 시설 이전이 필요한 부지는 2027년까지 이전을 결정하고 택지 조성에 착수할 수 있도록 범부처가 역량을 결집해 추진상황을 집중 관리할 예정이다.  사업 속도 제고를 위해 2026년 중 국방연구원과 서울의료원, 강남구청 등 13곳에 대한 공기업 예비 타당성 조사 면제를 추진하고 국유재산심의위·세계유산영향평가 등 사전절차도 신속 이행할 계획이다. 아울러 국가가 서민주택 공급 등을 위해 추진하는 공공주택지구조성 사업은 국무회의 등을 거쳐 그린벨트(GB) 해제 총량에서 예외로 인정하는 방안을 5년 한시로 추진한다.  이와 함께 투기 방지를 위해  해당 지구 및 주변지역은 토지거래 허가구역으로 즉시 지정한다. 이를 토대로 투기성 토지 거래 등을 사전에 차단할 방침이다. 정부는 지구·주변지역에 대한 조사 결과 미성년·외지인·법인 매수, 잦은 손바뀜과 같은 이상거래 280건을 선별했으며 이에 대한 분석 및 수사의뢰 조치에 나섰다.   향후 정부는 올 2월 도심 공급 확대를 위한 신규 부지와 제도개선 과제를 발표할 예정이다. 아울러 올 상반기 중 '주거복지 추진방안'을 발표해 청년과 신혼부부 등을 위한 주택공급 확대방안을 내놓을 방침이다.   donglee@newspim.com 2026-01-29 11:00
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서울 중소형 아파트값 고공행진…한강 이남 평균 18억 '돌파' [서울=뉴스핌] 정영희 기자 = 서울 한강 이남 지역 중소형 아파트(전용 60㎡ 초과~85㎡ 이하) 평균 가격이 18억원을 넘어섰다. 대출 규제 속에서도 상급지 수요가 이어지면서 중소형 면적을 중심으로 가격 상승 흐름이 지속되고 있다. [서울=뉴스핌] 양윤모 기자 = 서울 노원구 상계동의 한 아파트 단지 2025.10.24 yym58@newspim.com 2일 KB부동산에 따르면 지난달 한강 이남 11개구(강남·서초·송파·강동·양천·강서·영등포·동작·관악·구로·금천구)의 중소형 아파트 평균 매매가는 18억269만원으로 집계됐다. 전월(17억8561만원) 대비 0.96% 상승한 수치인 동시에 서울 중소형 아파트 평균 가격이 18억원을 넘어선 것은 이번이 처음이다. 실거래 사례에서도 가격 상승 흐름이 확인된다. 서울 서초구 방배동 삼호한숲 전용 84.87㎡는 지난달 27일 18억1000만원(4층)에 거래됐다. 같은 단지·면적 기준 종전 최고가였던 2023년 5월 2일 15억2000만원(11층)과 비교해 약 3억원 오른 금액이다. 강동구 명일동 삼익그린2차 전용 84.75㎡ 역시 지난달 26일 20억원(8층)에 팔리며 처음으로 20억원대를 기록했다. 지난해 10월 동일 면적이 19억1000만원(3층), 19억5000만원(2층)으로 잇달아 계약된 이후 약 3개월 만에 가격이 한 단계 더 올라섰다. 한강 이북 지역에서도 중소형 아파트 가격 상승이 이어지고 있다. 지난달 한강 이북 14개구(종로·중구·용산·성동·광진·동대문·중랑·성북·강북·도봉·노원·은평·서대문·마포구)의 중소형 아파트 평균 매매가는 지난해 12월(10억9510만원)보다 0.83% 상승한 11억419만원을 기록했다. 최초로 평균가가 11억원 이상으로 올라왔다.  서울 노원구 공릉동 태릉해링턴플레이스 전용 84.98㎡는 지난달 20일 11억9500만원(12층)에 계약되며 해당 면적 기준 최고가를 새로 썼다. 지난해 11월 거래된 종전 최고가 11억6000만원(15층)보다 3500만원 뛰었다. 은평구 수색동 DMC파인시티자이 전용 74.78㎡도 지난달 14일 12억9300만원(2층)에 거래됐다. 비슷한 면적인 전용 74.84㎡가 지난해 11월 22일 12억4500만원(3층)에 팔린 것과 비교하면 약 2개월 만에 5000만원가량 올랐다. chulsoofriend@newspim.com 2026-02-02 11:54
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