RDP 9208: Credit Supply and Demand and the Australian Economy 2. Business Credit and Investment

Investors often do not have sufficient information to assess the riskiness of investing in small and medium-sized companies, or such information may be too expensive to gather. Hence many companies find it prohibitively expensive to raise funds in open capital markets by issuing their own debt or equity. Financial intermediaries, such as banks, play a key role in providing credit to these enterprises over the business cycle.[3] They collect savings and allocate credit, with lending rates to particular firms reflecting their relative riskiness. Nevertheless, financial intermediaries, which specialise in assessing the potential riskiness of borrowers, may at times lack information to assess risks fully, and may find it in their own interest to ration credit.

2.1 Loan Supply and Demand with the Possibility of Credit Rationing

Debt contracts deal in promises to pay interest and repay principal in the future. If the risk associated with any project was known equally by both parties, and the borrower's behaviour could be monitored perfectly, the issuance of debt would be straightforward.[4] In the absence of official regulations, intermediaries would set prices to reflect known risks and demand would be equated with supply at that price. However, the efficient allocation of credit via interest rates presupposes that information about borrowers' projects is freely available. In practice this is not the case because of the presence of asymmetric information – borrowers know more about the risks associated with their projects than do banks and have an incentive to act in a manner which is not in the interests of the lender. This gives rise to a costly state verification problem as in Townsend (1979, 1988). Whenever there is an asymmetry of information between borrowers and lenders, optimal financial arrangements will involve deadweight losses which are referred to as “agency costs”. These include adverse selection and moral hazard costs (see below), but also all other transactions and information costs.

The existence of agency costs has two related implications for the behaviour of bank lending: (i) the potential for equilibrium credit rationing (as in Stiglitz and Weiss (1981)); and (ii) the cyclical movement of bank lending and interest rates. Both factors may combine to accentuate the business cycle.

Considering the first of these, the interest rate charged by a bank may itself influence the riskiness of the banks' pool of loans. As interest rates rise there are two effects at work:

  • the quality of the borrower pool declines as prudent investors drop out of the loan market. The borrowers who are willing to pay the higher interest rate are those with the riskier projects, with potentially higher returns, but they have to repay the loan in fewer states (between “good” and “bad” economic outcomes) of the world. That is, adverse selection occurs; or
  • borrowers may undertake riskier projects at higher interest rates (with potentially higher returns but lower probabilities of success). That is, a moral hazard problem arises.

Thus, as contractual interest rates rise, the bank's expected return on loans at first rises. But beyond some point the deterioration in the borrower pool begins to outweigh the direct gains from the higher contractual rates. This also implies that the variance of loan returns rises with interest rates, as default rates increase. This is illustrated by the backward bending loan return frontier in the top section of Figure 1, where expected returns peak at the rate rm, while the variance of returns (shown along the horizontal axis) rises.[5] Beyond some interest rate the expected return to the bank falls because anticipated increases in defaults more than offset any increase in interest receipts. At this point increased loan demand would cause the bank to maximise profit by denying loans to some companies, even though these could not be distinguished from firms receiving credit. Price rationing is abandoned in favour of equilibrium quantity rationing.[6]

Figure 1
Figure 1

The corresponding loan supply curve is shown in the bottom panel of Figure 1. The cost of funds to the bank, if, is a weighted average of low cost deposits and wholesale funds (raised at the riskless market rate i), set by monetary policy. The supply curve is not defined at lending rates below if. As the loan rate rises above if supply at first increases. The supply curve S0 becomes backward-bending at some point, as expected returns diminish.

The second aspect of agency costs is their cyclical nature. They are likely to decline when borrowers are more solvent, and rise as solvency declines (Bernanke and Gertler (1989)). Solvency is a function of factor prices and profits, which are driven mainly by the business cycle. Most defaults, for example, occur during economic downturns. Hence, agency costs are cyclical, declining in booms (as borrowers net worth and hence collateral rises) and rising in recessions (as borrower net worth and collateral declines). Thus a recession would be reflected in a downward shift and flattening out of the loan return frontier. That is, at each interest rate the expected return to the bank would be lower and the variance of returns higher.

If the portfolio problem faced by the bank is restricted to a choice between investing in a low-risk asset at rate i determined by monetary policy, or lending to a firm, it will wish to be on the optimal frontier. The efficient portfolio frontier faced by the bank is the line drawn from i to the point on the loan return frontier corresponding to the interest rate that equates loan supply and demand – for example, initially the frontier is the line from i to point B in Figure 1.[7] The bank will choose a point on the efficient frontier, i.e. a mix of riskless bonds and loans, such as point A, where its overall portfolio return lies somewhere between i and the expected return on riskier loans r1.[8]

Now consider the case in which a downturn in economic activity reduces firm profitability and increases agency costs. The increase in agency costs is reflected in the downward shift and flattening of the loan return frontier (the broken curve). At any given interest rate the bank would make less funds available – lending standards would be tightened – and the supply curve shifts from S0 to S1. For illustrative purposes, assume that loan supply is equated to demand at the higher interest rate i2. Suppose in this case that the efficient frontier is the line from i to the point of tangency at D. The higher loan rate enables the bank to achieve the same overall risk-return trade-off at point A (where it would hold a greater proportion of its portfolio in bonds and less in loans, since the latter are now riskier). The margin between the bank loan rate and the risk free rate rises from (i1 – i) to (i2 – i). The increase in the margin between the loan rate and other market rates are risk premia that reflect increased probabilities of default as the economy moves into recession. While the market for loans is cleared at the rate i2 in this example, any further increase in loan demand would lead to a state of excess demand. This is because at interest rates above i2 the bank's loan supply curve becomes backward bending, and equilibrium credit rationing would come into effect.

However, rationing may be unlikely in practice. In the above analysis, rationing requires relatively strong loan demand at a time of rising agency costs. Since agency costs are cyclical, loan demand is more likely to be very weak during recessions when such costs are highest. The demand curve is much more likely to move inwards to a position such as D1 when a downturn in activity shifts the supply curve inwards. But while rationing seems implausible in practice, the above analysis did demonstrate that there may be a cyclical risk premium in the loan rate, which could serve to exacerbate the business cycle. The economic cycle affects the net worth and hence collateral of the company sector as a whole. Default risks that arise from the cyclical behaviour of the aggregate economy cannot be diversified away by financial institutions. As the economy enters a downturn corporate net worth falls, raising agency costs and hence the loan rate relative to the riskless interest rate. This reduces investment and magnifies the extent of the contraction in activity. This process is reversed during an upturn in activity.

A general specification of the loan supply function consistent with the above discussion may be written as:

where: Inline Equation.

The first term states that loan supply depends on the sum of deposits and the book value of financial institutions' capital at the beginning of the period Dt−1. The second term, the banking sector share price relative to the market average (eb/e)t−1, captures the stockmarket's assessment of the relative expected profitability of banks and other financial intermediaries. This determines the ease with which new capital can be raised to finance loans in the forthcoming period. The third term, Et−1, is the market capitalisation of corporate equity at the beginning of the period. This affects the net worth of the corporate sector and hence the collateral available to banks – the higher is corporate net worth, the more collateral is available, and the more willing are banks to extend loans. The fourth term is the lending rate minus the weighted average cost of funds in the current period (iL – if)t. The higher the loan rate relative to the cost of funds, the better is the bank's average profit margin, and the more desirable is lending up to the point where the supply curve becomes backward bending.

The above discussion also suggests that during cyclical downturns agency costs rise, so that banks increase the loan rate relative to the current market interest rate, which is also the marginal cost of financing new loans. This cyclical risk premium is captured by the lending rate minus the certificate of deposit rate (iL – i)t in the current period. Such quality spreads have been found by Stock and Watson (1989), amongst others, as useful forecasters of swings in activity – a rise in the spread leading a downturn in activity. In Australia's case the loan rate minus the CD rate has also led fluctuations in the output gap since 1983 (Chart 2). The term is an imperfect measure of the risk premium, however, as it may have been affected by other factors. For example, the higher cost of traditional deposits as competition between banks has increased might have served to raise the margin between the loan rate and the CD rate independently of cyclical agency costs. For this reason other variables purporting to capture risks relevant for banking were also included in the equation.

The sixth term is the variance of bank share prices relative to the market average, σt. Any increase in the variance of expected returns on a bank's loan portfolio (the horizontal axis of the upper panel of Figure 1) should also be reflected in bank share prices. The seventh term πt is the expected inflation rate. This is a more forward-looking variable associated with lending risks. High inflation is likely to be associated with asset price speculation and the misallocation of real resources. It is possible that banks may be relatively more cautious lenders, other things being given, in a high-inflation environment.

On the demand side of the market for loans, debt financing by companies depends on expected future investment and relative prices:

where: Inline Equation and Inline Equation

and Inline Equation is future investment demand expected in period t; iLt is the loan rate in period t; Ept is the cost of equity finance in period t, proxied by the earnings-to-price ratio; and πt is the inflation rate expected in period t.

It is important that the investment spending variable used in the study of business loan demand is a forward-looking expectations series (Laffont and Garcia (1977), Sealey (1979)). These are proxied, somewhat imperfectly, by the Confederation of Australian Industry and Westpac Banking Corporation survey series. Given expected investment, the demand for loans from financial intermediaries also depends negatively on the lending rate. Higher lending rates for a given rate of inflation cause investment plans to be delayed. Lower lending rates cause them to be brought forward in time. This intertemporal substitution is a key element of the monetary policy transmission mechanism. Its effects should be seen first in observed borrowing behaviour, before actual spending and activity adjusts (see below). Changes in the earnings-to-price ratio induce substitution effects between debt and equity. A higher ratio is associated with a higher cost of equity and substitution towards debt financing. Finally, the demand for loans depends positively on inflation expectations (the expected future change in the relative price of goods).

The above loan supply and demand functions can be estimated with limited dependent variables methods, using the likelihood function derived by Maddala and Nelson (1974), (see Appendix A for a full technical exposition). The requirement that the interest rate adjusts to clear the market for loans is not imposed. Instead the loan rate enters as an explanatory variable, but instruments are applied to deal with simultaneity between supply, demand and the price of loans (the instrumental variables are described in Appendix B). Estimation requires the assumption that the observed quantity of loans transacted is the minimum of supply or demand. The technique permits the probabilities that each observation belongs to the supply or demand function to be derived, enabling the parameters of both to be estimated by maximising the likelihood function. Because most of the variables contain a unit root, the model is estimated in an error-correction form, where the lagged-dependent is included. Data definitions and issues are detailed in the Data Appendix.

2.2 The Behaviour of Business Credit Since the Early 1980s

The results for the model estimated on monthly data from December 1982 to July 1991 are presented in Table 1. All of the parameters of loan demand and supply have the expected signs and appear to be reasonably well determined.[9]

TABLE 1: Limited Dependent Variable Estimates of Loan Supply and Demand
Inline Equation
Inline Equation
(Sample Period: December 1982-June 1991; Monthly Data)
  Demand Supply
Constant 9.598 (28.4) −47.739 (16.0)
Lagged AFI credit to business ln Lt−1 −0.01 (6.9) −0.114 (384.7)
Investment expectations Inline Equation 0.024 (7.1)    
Overdraft rate iLt −0.151 (2.8)    
Inflation expectations πt 0.438 (3.4) −0.378 (5.1)
Earnings/price ratio Ept 37.843 (1.5)    
Broad money plus capital ln Dt−1     0.102 (95.6)
Corporate net worth ln Et−1     0.051 (75.9)
Relative bank share price ln(eb/ln e)t−1     4.185 (3.1)
Loan rate less weighted cost funds (iL−if)t     0.327 (0.6)
Loan rate less CD rate (iL−i)t     −0.372 (0.8)
Relative bank share price variance σt     −1.492 (6.7)
Log likelihood −107.018
R2 (for min (S, D) vs actual per cent change outcome) 0.45
Standard error of estimate 0.783

Note: Details of the estimation procedure are outlined in Appendix A. The current loan rate is treated with instrumental variables since in principle it is simultaneously determined with supply and demand. Details of instruments are set out in Appendix B. Approximate t-statistics are shown in parenthesis. Credit, broad money and corporate net worth are logged and multiplied by 100.

The estimated percentage excess of demand over supply is shown in the top panel of Chart 1. The only evidence of excess demand, or credit rationing, is during the 1983 recession. At this time the financial system was still in the process of moving from a regulated to a more liberalised state. To the extent that rationing was present at this time, it was more likely to have been of a disequilibrium variety related to the remaining effects of regulations. Interest ceilings on bank deposits were removed, credit directives ceased by the middle of 1982, and competition for deposits began to increase. This was reflected in a marked rise in the loan rate shown in Chart 2A, which was an important factor in the elimination of any excess demand that may have existed before 1984.

Chart 1A: Excess Demand
(percentage by which demand exceeds supply)
Chart 1A: Excess Demand
Chart 1B: Actual and Modelled Business Credit
(monthly log changes)
Chart 1B: Actual and Modelled Business Credit
Chart 2A: The Nominal and Real Loan Rate
Chart 2A: The Nominal and Real Loan Rate
Chart 2B: The Differential Between the Loan Rate and the CD Rate and the Output Gap
Chart 2B: The Differential Between the Loan Rate and the CD Rate and the Output Gap

Note: The output gap is obtained as the difference between the log of actual and smoothed output, where smoothed output is the result. of applying the Hodrick-Prescott filter to the log of actual output (see Hodrick and Prescott (1980)).

In the deregulated period from early 1984 onwards, there is no evidence of excess demand. Indeed, estimated supply has exceeded demand on occasions by about 1–2 per cent. Such outcomes are theoretically plausible, because loan demand is influenced by the level of interest rates, whereas loan supply depends on interest margins and other factors such as corporate net worth, bank profitability, etc. In terms of the analysis in Figure 1, if the supply curve was S0 and the demand curve was D1, excess supply FG would exist at the interest rate if. However, these circumstances do not seem very plausible in practice. As noted earlier, in a cyclical downturn both supply and demand functions tend to move inwards, reducing the likelihood of excess supply or demand. Since the excess supply finding is typically relatively small, given the standard error of the model, it is concluded that the market for business loans appears to have been broadly in equilibrium since 1984.

The second panel of Chart 1 shows monthly percentage changes of business credit from December 1982 and the model estimates of this series. The model appears to fit the data rather well, as reflected in the R2 and the standard error. Two broad episodes stand out:

  1. the rise in business credit growth to monthly rates of about 2 per cent (24 per cent at annual rates) from 1984 to the end of 1988 (though somewhat more slowly in 1987); and
  2. the marked decline in business lending from early 1989 to the end of 1991, when lending growth eventually became negative.

In explaining the rise in loan demand in the first episode, investment expectations appear to have been important. Chart 3 shows three-month ended growth in AFI credit to the business sector and the CAI-Westpac investment expectations net balance series. Investment expectations rose from 1984 and, while dipping in 1986, remained high until early 1989, when they began to decline very steeply. The model explains the strength of the demand for business credit through 1986, in spite of weaker investment expectations, mainly through its inflation term. Business borrowing, at the time, was strongly related to the asset price speculation and takeover activity usually associated with an inflationary environment.

Chart 3: Investment Expectations and Business Credit
Chart 3: Investment Expectations and Business Credit

Note: Investment expectations are measured as the net balance of survey respondents who expect their capital expenditure on buildings, plant and machinery to rise over the following twelve months, as reported in the CAI – Westpac Survey of Industrial Trends.

On the supply side, the interaction between perceived bank profitability and the net worth of the corporate sector were, according to the estimated model, important factors. Chart 4 shows the bank share price relative to the All Ordinaries index, and the market capitalisation of corporate equity. Financial liberalisation was associated with a sharp rise in the perceived profitability of banks in the early 1980s, with their share price rising 50 per cent relative to the market average. However, at that time the net worth of the corporate sector had not begun to increase significantly, as the economy was in recession. From 1984 corporate net worth did begin to grow rapidly and, given the perceived profitability of banks, credit supply rose in line with increasing demand. In 1986 and the first half of 1987, bank share prices declined relative to the average, largely in response to tight monetary policy. In liberalised financial markets higher interest rates increase the probability of non-performing loans. Since banks' balance sheets are directly affected, their share prices tend to be relatively adversely affected during such episodes. However, credit supply continued to grow rapidly despite the change in the relative market valuation of banks. According to the model presented here, this was due to the abnormal behaviour of corporate net worth. From January 1986 to October 1987 the market capitalisation of listed corporate equities grew from $100 billion to over $300 billion. This greatly increased the collateral of the corporate sector, thus offsetting the impact of high interest rates on bank share prices.

Chart 4: The Bank Share Price Index Relative to the All Ordinaries and the Market Capitalisation of Listed Equities
Chart 4: The Bank Share Price Index Relative to the All Ordinaries and the Market Capitalisation of Listed Equities

Credit supply remained strong after the stockmarket break in October 1987, when corporate net worth fell and agency costs should have risen. However, banks came back into relative favour with the stockmarket throughout the second half of 1987 and 1988, when there was a marked recovery in their average share price compared to the All Ordinaries index. The reasons for this improvement in the relative performance of banks were twofold. First, the favourable effects of the easing of monetary policy in 1987 and, after the stockmarket collapse, the Reserve Bank's announcement (in line with similar announcements in other countries) to guarantee the liquidity of banks. Second, dividend imputation was introduced in mid 1987. This was particularly favourable for banks because most of their dividends are fully franked. The improved market perception of the economic position of banks, then, helped underpin continued lending to the corporate sector during late 1987 and 1988. Demand remained particularly strong at this time because investment expectations had not been undermined, and the stockmarket break greatly increased the cost of equity finance (proxied in the model by the earnings-to-price ratio).

In the second major episode, business credit began to slow at the end of 1988, about one year after the stockmarket crash. On the demand side this was due to high real interest rates (Chart 2A), falling investment expectations and eventually declining inflation (Chart 3). On the supply side, corporate net worth did not fully recover after the stockmarket crash and, from the end of 1988, non-performing loan problems have seen bank share prices steadily decline relative to the All Ordinaries, as their profitability has been re-assessed. A credit crunch episode, in the sense of banks denying loans to borrowers regardless of the price they are prepared to pay for them, was not identified for this period, suggesting that the slowdown in credit growth was driven by a fall in the demand for loans rather than an excessive fall in supply. However, tougher lending standards operating through the normal price mechanism do appear to have been important. In cyclical downturns it is normal that lending rates should rise relative to the market rate underpinned by monetary policy. As shown in Chart 2B, the loan rate minus the CD rate led the downturn in activity, reflecting to a large extent the normal cyclical risk premium discussed earlier.

2.3 The Relationship Between Business Credit and Investment

The above results suggest that business credit supply and demand have been roughly in balance since the end of 1984. Credit demand was driven by expected future investment spending, the earnings-to-equity-price ratio, inflation expectations and the cost of credit. Moreover, supply was driven in large part by corporate net worth and bank share price behaviour – equity prices being determined by expected future returns. Cyclical risk premium were also found to be important. In other words, major influences on business credit are driven by variables which are (i) dependent on expectations about future activity (share prices, risk premia), or (ii) influence future activity, such as the intertemporal substitution effects induced by variations in the loan rate. In the absence of constraining regulations, these forward-looking influences suggest that business credit, in principle, should contain useful information for forecasting future business spending.

There is a certain cash-in-advance element to investment good purchases. Most capital goods, for example are imported, and it is necessary to make a succession of payments from the time orders are placed until the import and investment is recorded by the Statistician. Domestic orders of heavy machinery are counted as stocks of work in progress of the producer. Payments again need to be made, but the good is not recorded as investment until later. In liberalised financial markets these payments are more likely to be made at the discretion of companies through borrowing. Firms are not liquidity constrained in the sense of being dependent on cash flows or liquidity generated by the upswing in the economic cycle itself.

In a recession lending rates are relatively high due to the previous stance of monetary policy and increased cyclical risk premia, while cash flow is relatively poor. As it becomes clear the economy will recover, risk premia in lending rates begin to decline and asset values (and hence collateral begin to rise). At these times borrowing may be important in financing stock building and working capital in the initial stages of recovery. As the recovery gets under way and sales pick up, cash flow improves providing a contemporaneous accelerator boost to business investment later on. But in the initial stages of the recovery access to credit from financial intermediaries may play a pivotal role in financing investment in deregulated markets.

Conversely, at the top of the economic cycle a tightening of policy reduces expectations about future activity and profits, while increasing the cost of borrowing. Increased cyclical risk premia exacerbate the rise in the cost of credit and asset values fall. This leads to substitution towards internal sources of funds and reduced overall expenditure in the downswing phase. These factors ensure that the downswing will be contemporaneous with or led by a marked fall in borrowing from financial intermediaries.

Chart 5 shows 12-month-ended and 3-month-ended percentage changes in business credit and the 12-month-ended percentage change in business investment. The decline in growth of business credit in response to tight monetary policy in the late 1980s led the decline in investment by about one year.

Chart 5A: Nominal Investment and All Financial Intermediaries' Lending to Business
Chart 5A: Nominal Investment and All Financial Intermediaries' Lending to Business
Chart 5B: All Financial Intermediaries' Lending to Business (Break Adjusted) 3 month ended change
Chart 5B: All Financial Intermediaries' Lending to Business (Break Adjusted) 3 month ended change

The usefulness of business credit as a leading indicator of investment suggested by the above analysis may be tested explicitly. To do this, cointegration tests between the logarithm of business credit, the logarithm of nominal investment and the level of the loan rate were conducted to see whether there was a long-run equilibrium relationship between them.[10] The results (not reported) were decisively negative. This suggested that vector autoregression techniques were appropriate for testing the leading indicator properties of the changes in these series vis-a-vis each other. The results are set out in Table 2, using quarterly data over two sample periods: 1984Q1 to 1991Q2, when financial markets were fully deregulated and the loan market was not in a state of excess demand; and the full sample period 1977Q3 to 1991Q2. The null hypothesis is that the sums of the coefficients on the explanatory variables are zero. The table shows the estimated sum of the coefficients on the lagged variables and levels of significance of the F-statistics relating to the test of the null. The second statistics in parentheses are levels of significance for the test of the hypothesis that the coefficients on the lagged explanatory variables are jointly equal to zero.

TABLE 2: VAR Estimates: Nominal Investment, Business Credit and Overdraft Rate
  Business Credit Nominal Investment Overdraft Rate
Sample Period: 1984Q1–1991Q2
(Quarterly Data Lags = 3)
Dependent Variables
(0.00)** 0.243
(0.50) −0.001
(0.00)** −0.165
(0.88) −0.005
(0.95) 9.582
(0.72) 0.815
Sample Period: 1977Q3–1991Q2
(Quarterly Data Lags = 3)
(0.00)** 0.212
(0.03)* −0.000
(0.07) 0.138

(0.84) −0.006
(0.33) 5.291
(0.69) 0.934

Note: Business credit and nominal investment are in quarterly percentage changes. The overdraft rate is a quarterly average (in levels). The table shows the sum of the co-efficients on the lagged variables. The first figure in parenthesis is the significance of the F-statistic for the test of the null hypothesis that sum of the co-efficients is zero. The second figure in parenthesis is the level of significance of the F-statistic for the null hypothesis that the co-efficients on the lagged variables all equal zero. Significant F-statistics indicate rejection of the null hypothesis. Two asterisks denotes significance at the 1 per cent level. One asterisk denotes significance at the 5 per cent level. All variables are defined in the Data Appendix.

The results suggest some differences between the two sample periods. Over the full sample period investment appears to be a useful leading indicator of business credit. There is also some weaker evidence that business credit has useful information for forecasting changes in investment. However, if the sample is restricted to the shorter period of liberalised financial markets (and no excess demand), nominal investment no longer leads business credit. Instead, business credit becomes a very strong leading indicator for nominal investment. These findings are consistent with the view that during the 1980s loan supply and demand have come to be driven by more forward-looking variables, as financial markets have been liberalised.


Banks are also important lenders to large companies. But such companies can more readily substitute between different sources of financing in response to relative price movements. [3]

This is the well-known result of the Modigliani-Miller theorem. See Modigliani and Miller (1958). [4]

This diagram also assumes that borrowers accept a common loan size and that lenders are unable to distinguish amongst borrowers. [5]

For credit rationing to be effective in reducing investment, firms must be unable to raise funds in other ways, or other sources of funds must be less than perfect substitutes for bank loans. That is, firms cannot costlessly offset a decline in bank credit by obtaining funds elsewhere. [6]

The optimum frontier from the bank's viewpoint would be a line from i to the point of tangency on the loan-return frontier. But if supply exceeded demand at the interest rate corresponding to this point, competition would drive interest rates and expected returns down to a point like B. [7]

Note that the loan rate i1, corresponding to the expected return r1, is higher than r1. For a more complete derivation of the efficient portfolio frontier, see Greenwald and Stiglitz (1990). [8]

The standard errors calculated by the limited dependent variables method are only a guide to significance – see Appendix A. [9]

Business credit and investment appear to be integrated of order one. The loan rate appears to be stationary. Since the VAR results discussed below concern short-run changes in the logarithms of nominal investment and GDP, and since price deflators are relatively inert, most of the variation in these variables over the short-run concern real magnitudes. [10]