We present a model that attempts to explain this evidence by focusing on the role played by international credit constraints within an overlapping generations (OLG) endogenous growth setting. The model is able to generate either positive or negative growth eﬀects of capital inﬂows as well as a role for domestic savings for the success of liberalization policies. Contrary to the emphasis in much of the previous literature, our focus here is on countries whose autarky interestrate is above the worldinterestrate such that, when opening up, they would run current account deﬁcits. In this sense, our approach departs from the literature on the Lucas paradox, but comple- ments it by analyzing the growth eﬀects of capital inﬂows in deﬁcit economies. The endogenous growth setting also allows us to discuss long-run growth rather than sim- ply transitional dynamics. The model departs from the small open economy (SOE) setting assuming that foreign investment is restricted to be a percentage of the cap- ital stock of the economy. 2 This restriction is exogenous, and we use changes in it to model capital account liberalizations. However, the amount agents can borrow in international credit markets is endogenously determined. 3 In this framework, agents cannot commit with collateral and there are enforcement constraints that determine the amount agents can borrow on the credit markets. Our endogenous growth setting has a reproducible factor that generates externalities and leads to permanent growth
A change in inequality has an ambiguous effect on the market for the primary commodity. However, notice that the above expression is positively related to the level of agency costs. The last term of the above expression captures the boost in the demand for external finance by wealthy agents who become wealthier after the increase in inequality. In economies with poor quality financial institutions entrepreneurs can raise less external finance for any given amount of internal funds and thus this effect might be dominated. In the following example we use, once more, the same parameters as in Example 1 and we set the worldinterestrate equal to the autarky price. As before, the qualitative results would remain the same for small changes in the worldinterestrate in either direction thus will remain unaffected by the direction of capital flows.
In Comparison, these studies did not cover the period of the recent global financial crisis beginning in 2008. The study by Cho and Kang (1999) did not distinguish between loan demand and loan supply. Although Kim (1999) separated loan demand and loan supply, he did not consider global factors such as the exchange rate and the foreign interestrate. In addition, this paper adopts a simultaneous-equation model consisting of bank loan demand and supply, incorporates global factors such as the exchange rate and the worldinterestrate, applies the more advanced three-stage least squares method, covers more recent periods including the global financial crisis, and yields statistical results that are consistent with the expected hypotheses.
Implicit in the investment rule of the basic theory is the view that individual investors either do not face investment risk or, if they do, they do not care about it. This is why their only objective when choosing a portfolio is to maximise its return. But this is clearly a simpliﬁcation. In the real world, investors face a trade- off between maximising the return to their portfolio and minimising its risk. They are in general willing to buy assets that offer a low return if these assets allow them to hedge part of the risk in their portfolios. To make this observation operative, I shall modify the assumption on how countries choose their portfolios as follows: invest your wealth in domestic capital until its marginal product equals the worldinterestrate plus the appropriate risk premium. Investors require the latter as a compensation for the risk associated with real investments. 13
Following Galor and Zeira (1993), we study the effect of the worldinterestrate on inequality and growth for the period 1985-2005, char- acterized by falling worldinterest rates and cross-country income po- larization. We argue that the two phenomena are related on the basis of the following findings, which are in accordance with the predictions of the Galor and Zeira model: 1) a reduction of the worldinterest rates increases inequality in rich countries and decreases inequality in poor countries; 2) inequality has a negative (and significant) effect on hu- man capital accumulation in rich countries and a positive (but mostly not significant) effect in poor countries; 3) human capital positively affects GDP in both group of countries, in particular with a higher marginal effect in poor countries. The overall effect of these facts is polarization in the world income distribution.
Both the fixed and floating interest legs are calculated according to Australian money market conventions (act/365 fixed). The floating amount is calculated on a compounding basis using the RBA30 rate fixes. Settlement is 1 st day after termination date. For an OIS of term greater than one year , both floating and fixed payments are settled annually.
Indeed, the question: Could commercial banks maintain the purchasing power of people's savings during a specific period of time? raises the idea of the compensation rate. In the past, however, during the commodity standard (gold is the commodity usually associated with a commodity standard), this question could not be that sensitive. This is due to the fact that, under the gold standard a unit of money is specified as a given weight of gold. Therefore, in that system, the monetary price of commodity (gold) is fixed. Hence, during inflationary periods, the monetary price of gold, would automatically neutralize the declining purchasing power of money. Of course it is true that under the gold standard monetary authorities tried to stabilize the gold price, but they never completely succeeded. In the modern monetary system, during times of inflation, the purchasing power of money would, without any compensative factor, decline. This element would continually damage saving and time deposits of people. The owners of these deposits enjoy a couple of bank services, though.
It may be observed in Figures 1 and 2 that except for the year 2009 marked by the credit crunch and 2010 characterized by comfortable liquidity conditions in the banking system, the lending rates (short and long-term) were fairly stable and varied within a narrow range, while the deposit rates, the Treasury bill and the repo rates were more volatile and displayed stronger fluctuations. This contrasting behavior of the lending and other rates whereby lending rates seem to follow an independent development path, may be explained by the fact that the lending rates are unresponsive to changes in the policy rates because they are determined by factors other than the cost of funds, while the deposit rates are sensitive to changes in the policy rates and exhibit similar developments. As stated by the National Bank of Rwanda in a recent policy document, the weak responsiveness of the lending rates to changes in the key repo rate is due to, among other factors, high operating costs in the banking sector and high provisions for bad loans. In addition, behavior of borrowers such as lack of information on loan conditions and culture of not bargaining with banks contributed to the rigidities in lending rates charged by banks (NBR, February 2015).
The empirical analysis exploits a novel daily data set of SNB Bill auctions to identify the dynamic causal effects of an interestrate floor shock. From 2008 to 2011, the Swiss National Bank (SNB) auctioned debt securities on a pre-determined weekly schedule to soak up reserves created in emergency liquidity provisions and foreign exchange interventions. We propose to estimate dynamic causal effects combining identification through heteroscedasticity (Rigobon 2003) with local projections or vector autoregressions (Jord`a 2005; Stock and Watson 2018; L ¨utkepohl 2012; L ¨utkepohl et al. 2018). A restrictive interestrate floor shock causes an increase in the money market rate, a persistent appreciation of the Swiss franc, a decline in stock prices, and a decline in long-term interest rates. One interpretation of the decline in long-term interest rates is that markets expected money market rates to remain persistently low because of the restrictive impact of the appreciation. In addition, we perform policy experiments in which the central bank raises the interestrate floor from
The first conundrum we shall discuss in fundamental term-structure modeling is to distinguish the risk-free and default-free curves. Though most literature treat the two curves indifferently with a reason that buying and holding a default-free asset creates a risk-free return, risk-free and default-free assets bear very different mean- ings since only the latter are tradeable. The HJM framework  provides a hint for improvement. First, by definition in , risk-free assets need to have zero volatility; hence it is necessary that η ≡ 0 for risk-free assets. Consequently, derived from the HJM framework, the volatility term of the risk-free curve needs to be (almost surely) zero at any time t if assuming the interest-rate volatilities are non-negative. In addition, the liquidity premium and bond volatilities must be zero for all risk-free bonds because they are not marketable. Hence, for a risk-free curve, H t T ( ) , ≡ 0 and G t T ( ) , = G t ( ) , 0 for all T since the forward risk-neutral measure coincides with conventional risk-neutral measure when bond volatilities are zero.
To integrate money into the structural growth model in , let’s assume that each agent needs money to maintain its production or consumption. The money-owners lend money to earn interest in each period and spend all the interest for consumption, just like land-owners lease land to earn land- rent. And the other consumers and firms also spend all their income for consumption or reproduction. An agent’s demand for money is assumed to be proportional to the value of the commodity bundle it purchases, hence the total demand for money depends on the price level and the activity level in the economy. For now the model excludes the mechanism that equalizes the profit rate and the interestrate as discussed in . That is, in an equilibrium the interestrate is allowed to be far away from the profit rate of firms.
Mortgage backed security interestrate swaps are agreements between two counterparties based on a bundle of mortgages: commercial, residential or other debts. These bundles are often packaged and securitized by agencies but can also be created by other commercial lending institutions. The interestrate payments are based on the monthly payments made by borrowers to the owners of mortgages, minus any fees or spreads by payment service companies. The primary risks are duration, prepayment, and failure to pay by the borrower.
Firm A pays 5.5% (to B) on its SFr150 million loan. But firm A also pays 10.0% interest on its US$ bonds while receiving 10.75% interest on its US$100 million loan to B -- or a net inflow of 0.75%. Thus, A pays (approximately) 4.75% net interest on its SFr loan. This represents a 0.25% savings in relation to its own cost of borrowing SFr.
Paralleling the explosive post 1970s growth of international capital flows has been the sharp rise of long-term real interest rates. The figures in Table 4 on U.S. long- term real rates give an indication of the world-wide pattern. As we see in the table, the 10-year Treasury Bond rate spiked at an average of 5.9 percent between 1980-84, after having ranged between 0.8 – 2.7 percent over the five year periods between 1955-79. The rate does fall in subsequent five-year periods after 1980-84, though by 1995-99, only to a still historically high 4.3 percent. In 2000 – 04, the most recent full five-year period, the rate then falls to 2.7 percent, which is at the level of 1960 – 64. But as we have seen, this was due to the Federal Reserve also pushing the Federal Funds Rate to its lowest levels in 50 years, in order to counteract the stock market crash and recession of those years.
The data used in this research consist of average monthly series of two policy rates, namely the Treasury bill rate of different maturities (from one to six months) and the Repo rate along with three bank rates (interbank, deposit and lending rates) collected from tables published by the National Bank of Rwanda. Interbank rate, deposit rates of different maturities (from one to six months) and lending rates of short, medium and long term have been considered for analysis. The data cover the sample period 2008-1 to 2016-12. This period has been chosen for two main reasons. First, the repo rate was introduced in 2008 as a new monetary policy instrument. Second, during this period, the main reforms in the financial system had been completed and the Central Bank had gained its full independence and relied more on the interestrate for conducting monetary policy. The choice of policy variables can be motivated as follows. In the current monetary policy framework, the key repo rate is the instrument used to signal the monetary policy stance of the Central bank. However, the key repo rate is announced on a quarterly basis and may remain unchanged for long time periods, which makes it less suitable for econometric purposes. By contrast, the Repo rate is dynamic since it is used by the NBR in the open market operations as the main instrument to signal the financial conditions in the money markets on a daily basis; therefore, the Repo rate is considered as the main policy rate in this study. The Treasury bill rate of different maturities has also been used as policy rate since it has been argued in the literature that in the long-run, banks set their retail prices in line with their marginal cost, i.e. the funding cost on loans and opportunity cost of deposits, which can be best estimated by money market rates reflecting market conditions (De Bondt, 2005).
observed from the plot of the series (see Figures 1 and 2) and their influence on the nexus. There are also theoretical considerations for why structural breaks could matter for the nexus of concern. Considering the growing integration of the world economy and the special economic cooperation between the G7 economies, the example of the global financial crisis and its aftermath could fuel concerns regarding the sensitivity of the nexus to policy shifts in the area of study. To this end, we categorize the G7 countries into euro area and non-euro area countries and hypothesize that the significance, or otherwise, of asymmetries and structural break in the nexus can vary between the two categories. We expect this unevenness between the euro and non-euro area countries, given the spillover impacts of U.S. monetary policy (the reference country) to the euro area and the bond between the euro/dollar exchange rate are empirically reported to be strong (Hanisch, 2019; Heimonen, 2009), whereas the same cannot necessarily be said of the non-euro area.
In 2018, inflation rate for Gambia was 6.3% though Gambia inflation rate fluctuated sustainably in recent years. The reflection of inflation as it is measured by the consumer price index shows the annual percentage change in the cost to the average consumer of acquiring goods and services that may be fixed or changed at specified intervals, such as yearly (IMF, 2018). However, the domestic foreign exchange market in The Gambia continues to operate smoothly despite the fluctuation of inflation and interest rates. Transaction volumes increased to US$2.1 billion in the year to March 2019 compared to 1.7 billion US dollars in the previous year. From January to March of 2019, volume of transactions amounted to 638.5 million US dollars compared to US$507.9 million in the last quarter of 2018, this indicate an increase of 25.7% (CBG, 2019). In the first quarter of 2019, buying of foreign currency increased by 18.1 % from a year ago. Furthermore, sales of foreign currency rose significantly by 20 % in the same period, thus showing a positive indication of Gambia economic outlook. Central banks need to understand the magnitude through which inflation and exchange rate can affect exchange rate fluctuations and further monitor the impacts it has on the economy as a whole. Many reasons have been discussed in the literature for the fluctuation of exchange caused by inflation and interestrate.