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Previous literature for the relations between the market interest rates and the targeted or target rate of the Federal Reserve paid little attention to Eurodollar market rates. The present paper attempts to fill this void.

The study investigates the dynamic relationship between the federal funds rate and three short‐term Eurodollar deposits rates. Cointegration analysis is utilized to examine the long‐run relationships between the short‐run dynamics of the market and targeted rates through a vector error‐correction mechanism.

The study shows strong evidence that, while the Eurodollar rates and the federal funds rate move together over time regardless of procedural differences in targeting, how they co‐move, especially how they adjust toward long‐run equilibrium, appears to be related to the targeting procedural changes.

Further research should be conducted for the theoretical analysis of strategic interactions between the monetary authority and market participants in the domestic and external financial markets.

The result suggests that the Fed may affect the market interest rates through a policy of changing the federal funds rate target by a “fixed” amount for the foreseeable future. Such a policy has improved the market's ability to predict the size and timing of the changes in the target rate.

The results of the paper give some new insights into the interactions between monetary policy operations and market interest rates, which is of interest to researchers, monetary authorities, and financial market participants.

The purpose of this paper is to analyze the effects of Swedish rent controls on observed vacancy rates for rental housing.

Housing vacancy rates are unevenly distributed among Swedish municipalities. In large expansive municipalities, such as Malmö, Göteborg and Stockholm, vacancy rates are very low, while in declining or smaller municipalities such as those in the northern and interior parts of Sweden, vacancy rates are considerably higher. This implies welfare losses not only in growing municipalities with queues for rental apartments but also in municipalities that are shrinking since the controlled rents there are higher than market rents and cause higher vacancy rates than with market rents. The authors estimate the influences of various determining factors, such as population growth, population size, rent levels, construction, demolition and market orientation of rents, on the observed vacancy rates.

The authors find that that these factors affect the vacancy rates differently depending on whether a municipality is large or small, growing or shrinking. Population growth, in percent per year, plays an important role in explaining the observed vacancy rates in declining regions.

A research task that remains to be done is to calculate the welfare losses due to rent higher than the market rent for municipalities in contraction.

To reduce the welfare losses of rent control, both in expanding and contracting municipalities, economists' straightforward recommendation to deregulate the rent control should, in principle, be carried out.

In many countries, rent control regulations are limited to cities, such as New York City. The paper shows that the Swedish rent control system however, applies nationwide, except for annual rent increases, which are set locally through negotiation.

The role of money and monetary policy of the central bank in pursuing macroeconomic stability has significantly changed over the period since the end of World War II. Globalization, liberalization, integration, and transition processes generally shaped the crucial milestones of the macroeconomic development and substantial features of economic policy and its framework in Europe. Policy-driven changes together with variety of exogenous shocks significantly affected the key features of macroeconomic environment on the European continent that fashioned the framework and design of monetary policies.

This chapter examines the key basis of the central bank’s monetary policy on its way to pursue and preserve the internal and external stability of the purchasing power of money. Substantial elements of the monetary policy like objectives and strategies are not only generally introduced but also critically discussed according to their accuracy, suitability, and reliability in the changing macroeconomic conditions. Brief overview of the Eurozone common monetary policy milestones and the past Eastern bloc countries’ experience with a variety of exchange rate regimes provides interesting empirical evidence on origins and implications of vital changes in the monetary policy conduction in Europe and the Eurozone.

The paper is motivated by the paucity of empirical research on the determinants of capitalisation rates/yield in the commercial property market. Compared to property price determinants, the capitalisation rate has received significantly less attention. This is somewhat surprising given that the capitalisation rate is a more insightful indicator for investors on commercial property market performance than merely price changes or trends. The capitalisation rate, measured as the ratio of net operating income to the property’s capital value, captures the asset’s overall ability to generate income which is crucial for investors who typically invest in property for their income-generating capacity. The purpose of this paper is to address these issues.

To evaluate the determinants of capitalisation rates, time series analysis was used. The data capture performance in the Australian commercial property market between 2005 and 2018. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation’s central bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration amongst some of the I (1) variables, the autoregressive distributed lag model was selected given its flexibility and relative lack of assumptions.

Bond rates, market risk premiums, stock market excess returns and other macroeconomic variables were found to drive capitalisation rates of Australian commercial properties. A 1% increase in the bond rate results in approximately 0.3–2.4% increase in capitalisation rates depending on the sub-market. Further, a 1% increase in excess market returns results in a 0.01–0.02% increase in capitalisation rates. Regarding risk premiums, a 100 basis point increase in the BBB spread results in approximately 0.92–1.27% reduction in cap rates in certain markets.

Asset managers will find these results useful in asset allocation strategies. Commercial properties offer attractive investment qualities such as yield stability in periods of economic uncertainty while allowing for the possibility of capital growth through appreciation of the underlying asset. By understanding the factors that affect the capitalisation rate, practitioners may predict emerging trends and identify threats to portfolio return and stability. This allows better integration of commercial property in the construction of portfolios that remain robust in a variety of market conditions.

The contribution to literature is significant given the lack of similar studies in the Australian market. The performance of real estate assets using cap rates as a comparative measure to equities and bonds influences decisions in asset allocation strategies. It provides crucial information for investors to estimate the performance of commercial property. This research supports the notion that both space and capital market indicators jointly affect capitalisation rates. The findings expand the knowledge base relating to commercial properties and validate the assessments of investors, developers and valuers who utilise yield as a performance benchmark for asset allocation strategies.

The transmission of monetary policy rates to lending rates is viewed as a crucial path of monetary policy. As an integral part of the financial system and the recent financial crisis, securitized assets have the potential to affect the interest rate pass-through process and monetary policy effectiveness. This paper aims to investigate the influence of securitization on the transmission of policy rate changes to lending rates and how rate transmission has changed since the recent financial crisis. Emphasis is placed on differences among the mortgage, consumer credit and business loan securitization markets and between agency and private-label securitization transactions.

The empirical framework is an error-correction model augmented to directly measure the influence of securitization. Monetary policy effectiveness is measured by the size and speed of transmitted policy rate changes to lending rates. An efficiency measure of relative adjustment accounts for differences in the size of long-run responses across loan markets and changes in efficiency from securitization within loan markets.

The size and speed of interest rate pass-through tend to increase with securitization. Liquidity, capital relief and funding from securitization help to make lending rates more responsive. Increases in pass-through with securitization are less in the consumer credit and business loan markets after the recent financial crisis relative to before the crisis. In contrast, mortgage markets tend to have larger pass-through after the financial crisis. Differences in rate transmission after the recent financial crisis point to the role on nonbanks in consumer credit and business loans and asset purchase programs of the Federal Reserve in mortgage markets. Securitization tends to make the adjustment process more efficient, and gains in efficiency from securitization are larger after the financial crisis.

A key contribution of the study differentiates securitization across markets and types to determine the effects on the interest rate pass-through process. The results show that increases in the efficiency of the adjustment process from securitization tend to be greater in mortgage markets and for all private-label securitized assets. These findings have implications for proposed government-sponsored entity (GSE) reform to reduce the role of GSEs in the housing market, promote private-label mortgage credit and strengthen securitization deals.

The purpose of this paper is to model interest rates from observed financial market data through a new approach to the Cox–Ingersoll–Ross (CIR) model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek framework. However, there are a number of issues in describing interest rate dynamics within the CIR framework on which focus should be placed. Therefore, a new methodology has been proposed that allows forecasting future expected interest rates from observed financial market data by preserving the structure of the original CIR model, even with negative interest rates. The performance of the new approach, tested on monthly-recorded interest rates data, provides a good fit to current data for different term structures.

To ensure a fitting close to current interest rates, the innovative step in the proposed procedure consists in partitioning the entire available market data sample, usually showing a mixture of probability distributions of the same type, in a suitable number of sub-sample having a normal/gamma distribution. An appropriate translation of market interest rates to positive values has been introduced to overcome the issue of negative/near-to-zero values. Then, the CIR model parameters have been calibrated to the shifted market interest rates and simulated the expected values of interest rates by a Monte Carlo discretization scheme. We have analysed the empirical performance of the proposed methodology for two different monthly-recorded EUR data samples in a money market and a long-term data set, respectively.

Better results are shown in terms of the root mean square error when a segmentation of the data sample in normally distributed sub-samples is considered. After assessing the accuracy of the proposed procedure, the implemented algorithm was applied to forecast next-month expected interest rates over a historical period of 12 months (fixed window). Through an error analysis, it was observed that our algorithm provides a better fitting of the predicted expected interest rates to market data than the exponentially weighted moving average model. A further confirmation of the efficiency of the proposed algorithm and of the quality of the calibration of the CIR parameters to the observed market interest rates is given by applying the proposed forecasting technique.

This paper has the objective of modelling interest rates from observed financial market data through a new approach to the CIR model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek model (Section 2). However, there are a number of issues in describing short-term interest rate dynamics within the CIR framework on which focus should be placed. A new methodology has been proposed that allows us to forecast future expected short-term interest rates from observed financial market data by preserving the structure of the original CIR model. The performance of the new approach, tested on monthly data, provides a good fit for different term structures. It is shown how the proposed methodology overcomes both the usual challenges (e.g. simulating regime switching, clustered volatility and skewed tails), as well as the new ones added by the current market environment (particularly the need to model a downward trend to negative interest rates).

The retention rate of a company has an impact on its earnings and dividend growth. Corporate management has control over this. However, lease structures in some real estate markets reduce the control of investment managers and force them to adopt full distribution policies and a passive management style. This is likely to impact the rental performance of the real estate by permitting depreciation to go uncorrected. This paper examines several European office markets across which lease structures and retention rates vary. It then compares depreciation rates across these markets. It is concluded that there is evidence of a relationship between retention and depreciation. Markets with particularly inflexible lease structures clearly exhibit low retention rates, and we can tentatively suggest higher levels of rental value depreciation. This poses interesting questions concerning the relationships between lease structures in different markets and their impact on expenditure by owners, and also concerning the impact on building depreciation and property performance. While longer and deeper datasets are necessary to establish direct linkages between lease structures and performance, this paper raises important issues for global investors.

The purpose of this paper is to empirically analyze the transmission mechanism between benchmark interest rate of financial market, money market interest rate and capital market yields in order to reveal the dynamic evolution characters and core influential structure between different market interest rates.

Using Dirichlet-VAR (DVAR) model, this study analyze the relationship between markets rates according to the equilibrium model in money market and capital market.

Empirical results show that the interest rate transmission mechanism functions smoothly between interest rates of different levels. Interest rate of bills issued by the central bank can effectively reflect changes in monetary policy and guide the fluidity of market, playing the anchor role in interest rate pricing. There exists a closed loop feedback between interest rate of bills issued by the central bank, and money market interest rate, as well as between money market interest rate and bond market interest rate. The former is a loop by administrative means while the latter is the one mainly affected by market-oriented means. The response by money market and bond market toward the change of benchmark interest rate is unsymmetrical as money market is more sensitive to a loose monetary policy while bond market is more sensitive to a tight monetary policy. Stock market is strongly affected by uncertainty of benchmark interest rate.

DVAR model is the extension of research on instable data and multiple variable causality test, which expands the causality analysis between two variables to multiple variables causality impact analysis which contains non-stable and structurally instable economic data.

This research examines how macroeconomic variables can precisely predict bull/bear stock markets in China and Taiwan.

This paper adopts a two-state Markov switching model to characterize the bull and bear markets spanning from 1994 to 2019 and then conduct a bear stock market predictability test by running regressions between the filtered probabilities of bear markets and a series of macroeconomic variables in turn at different horizons of 1, 3, 6, 12 and 24 months.

This paper shows that inflation rates, changes in real exchange rates, and foreign currency reserve growth are key predictors of bear markets in China, while term spreads, unemployment rates and foreign reserve growth are major factors that can predict bear markets in Taiwan. Remarkably, industrial production growth does not have predictive power for bear markets, which may suggest emerging markets are driven by fund flows rather than real economic activities. Besides, the impact directions of foreign currency reserve growth are opposite, which may be due to different proportions of the financial accounts in their balance of payments.

In practical respect, this paper provides market participants the usefulness, impact direction and implications of bear market predictors when building their market-timing strategies in China and Taiwan stock markets. The government institutions may also thereby make appropriate policies to prevent huge stock market downturns and serious drawbacks.

It highlights the “fund-driven market hypothesis” and “foreign currency reserve effects” that commonly dominate Taiwan and China stock markets since both are highly affected by international funds.

We analyze the impact of monetary policy instruments on interbank lending rates and retail bank lending in China using an extended version of the model developed by Porter and Xu (2009). Unlike the central banks of advanced economies, the People’s Bank of China (PBoC) uses changes in the required reserve ratios and open market operations to influence liquidity in money markets and adjusts the regulated deposit and lending rates and loan targets to intervene in the retail deposit and lending market. These interventions prevent the interbank lending rate from signaling monetary policy stance and transmitting the effect of policy to the growth of bank loans. Since the global financial crisis, the PBoC’s monetary policy has gone through a full cycle. The combining effects of using different policy instruments simultaneously within a short period of time were quite effective in bringing the credit and money growth in line with its desired level. Most recently steps have been taken to speed up the interest rate liberalization. Effective July 2013, the PBoC removed the floors of the benchmark lending rates.