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Inflation, Financial Deepening, and Economic Growth
By
Mohsin S. Khan *
International Monetary Fund
Paper prepared for the Banco de Mexico Conference on Macroeconomic Stability, Financial Markets and Economic Development, Mexico City, November 12-13, 2002. ___________________________________________________________________________ * I am grateful to Abdelhak Senhadji for helpful discussions on this topic. The views expressed in the paper are my sole responsibility and do not necessarily reflect the opinions of the International Monetary Fund.
I. INTRODUCTION
There is now almost a universal consensus in the profession that macroeconomic stability,
specifically defined as low inflation, is positively related to economic growth. Over the years
the question of the existence and nature of the link between inflation and growth has been the
subject of considerable interest and debate. Although the debate about the precise
relationship between these two variables is still open, the continuing research on this issue
has uncovered some important results. In particular, it is generally accepted that inflation has
a negative effect on medium and long-term growth. 1 Inflation impedes efficient resource
allocation by obscuring the signalling role of relative price changes, the most important guide
to efficient economic decisionmaking (Fischer (1993)).2
If inflation is inimical to growth, it obviously follows that policymakers should aim at a low
rate of inflation. But how low should inflation be? Should it be 10 percent, 5 percent, or for
that matter, zero percent? Or put in other words, is there a level of inflation at which the
relationship between inflation and growth become negative?
1 See Barro (1991, 1995), Fischer (1983,1993), and Bruno and Easterly (1998).
2 It has also been argued that what matters for efficient resource allocation is not so much the level of inflation but its variance. While theory seems to suggest that the variability of inflation should affect growth more than its level, empirical studies show the opposite result (see Fischer 1993).
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These are questions that several recent empirical studies have examined, focusing on whether
the relationship between inflation and long-run growth is in fact nonlinear. The hypothesis is
at some (low) rate of inflation, the relationship is nonexistent, or perhaps even positive, but at
higher rates it becomes negative. If such a nonlinear relationship exists then it should be
possible in principle to estimate the inflexion point, or threshold, at which the sign of the
relationship between the two variables would switch. Fischer (1993), in the seminal paper on
the subject, noted the existence of a positive relationship between long-run growth and
inflation at low rates of inflation, and a negative one as inflation rose. Following Fischer
(1993), there have been a number of formal empirical attempts to identify threshold effects in
the inflation-growth relationship. These include, for example, papers by Sarel (1996), Ghosh
and Phillips (1998), Bruno and Easterly (1998), and Khan and Senhadji (2001). These studies
generally find that for economies with initially low rates of inflation, modest increases in the
rate of inflation do not affect long-run rates of real growth. But for economies with initially
high rates of inflation, further increases in the inflation rate have adverse effects on real
growth. In the most recent study of this issue, Khan and Senhadji (2001) find that the
threshold rate of inflation is fairly low—around 1-3 percent for industrial countries, and
7-11 percent for developing countries. With these estimates it is now possible to define
“macroeconomic stability” in quantitative terms, namely that it implies single-digit inflation.
How then does inflation affect growth, and more particularly, what gives rise to the so-called
threshold effect in the relationship? In a recent paper, Khan, Senhadji, and Smith (2001)
argue that the real effects of inflation derive from the consequences of inflation for financial
development, or “financial deepening”. There are good reasons to think so. First, there is now
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both empirical and theoretical literature suggesting that financial markets play an important
role in the growth process.3 Thus, if changes in the rate of inflation do affect financial market
development adversely, it is likely that such changes would also have implications for
growth. Second, there is also both theoretical and empirical literature suggesting why the
effects of increases in the rate of inflation on financial deepening might be very different at
initially low versus initially high rates of inflation.4
The theoretical underpinnings of the relationship between financial depth and growth can be
traced back to the work of Schumpeter ,5 and more recently, to McKinnon (1973), and Shaw
(1973). The main policy implication of the McKinnon-Shaw school is that government
restrictions on the banking system (such as interest rate ceilings, high reserve requirements,
and directed credit programs) hinder financial development, and ultimately reduce growth.
Similar conclusions are also reached by the recent papers on endogenous growth theory, in
which services provided by financial intermediaries (such as information collection and
analysis, risk sharing, liquidity provision, etc.) are explicitly modeled. 6 These papers show
convincingly that long-run economic growth depends on financial deepening.
3 See the recent surveys of this literature by Levine (1997) and Khan and Senhadji (2000).
4 This literature is reviewed in Khan, Senhadji, and Smith (2001).
5 See King and Levine (1993a).
6 For an explicit link between financial development and growth, see Greenwood and Jovanovic (1990), Bencivenga and Smith (1991), King and Levine (1993a), Roubini and Sala-i-Martin (1992), and Greenwood and Smith (1997). A comprehensive survey is provided by Levine (1997).
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The extensive empirical work on the relationship between financial development and growth
has been surve yed in Levine (1997). One of the more influential studies on the subject is
King and Levine (1993b), which shows a strong positive link between financial development
and growth. 7 King and Levine (1993b) also show that financial development has predictive
power for future growth and interpret this finding as evidence for a causal relationship that
runs from financial development to growth.
This paper argues that the nonlinear link between inflation and growth results from the
threshold relationship between inflation and financial deepening. It reviews the existing
theory and empirical evidence on the effects of inflation on growth and on financial
deepening. The unique aspect of the empirical estimates is that they are obtained using new
econometric methods for threshold estimation and inference. Therefore, they are more
reliable than previous estimates reported in the literature on the subject.
In what follows, Section II looks at the link between inflation and growth. Section III
examines the effects of inflation on financial deepening. The concluding section completes
the picture of the theoretical and empirical relationships among inflation, financial
deepening, and growth.
7 Related papers are Roubini and Sala-i-Martin (1992), Easterly (1996), and Pagano (1993).
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II. INFLATION AND GROWTH
To test for the existence of a threshold effect, Khan and Senhadji (2001) estimate the
following model:
ititititititit
ititititittiit
eXIId
IIdyd
++>−+<−
+>−+<−−++=
')}1()]log()[log()1()1{(
)}1()]log()[log()1()1){(1()log(*
2
*1
*
*
θπππππγ
πππππγµµπ
π
(1)
≤>
=*
*
01*
πππππ
it
itit if
ifd i=1,…,N; t=1,…,T
where dlog(yit) is the growth rate of real GDP,8 µi is a fixed effect, µt is a time effect, πit is
inflation based on the CPI index, π* is the threshold level of inflation, *π
itd is a dummy
variable that takes a value of one for inflation levels greater than π* percent and zero
otherwise, and I(πit <1) and I(πit >1) are indicator functionsthat is, functions that take the
value of one if the term between parentheses is true and zero otherwise. Xit is a vector of
control variables which includes investment as a share of GDP (igdp), population growth
(dlog(pop)), the log of initial income per capita (log(yi0)), the growth rate of terms of trade
(dlog(tot)), and the five-year standard deviation of terms of trade (Φtot). The index “i” is the
cross-sectional index while “t” is the time-series index.
8 The growth rate of a variable x is computed as the first difference of log(x).
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Note that Xit contains only the most important variables among the large set found in the
empirical growth literature because very few of these variables pass the robustness tests in
Levine and Renelt (1992) and Sala-i-Martin (1997). The effect of inflation on GDP growth is
given by γ1 for countries in which inflation is less or equal to π* percent, and γ2 for countries
with inflation rates higher than π* percent.
In order to smooth out business cycle fluctuations and focus on the medium- and long-term
relationship between inflation and growth, equation (1) has been estimated using five-year
averages of the data in a panel of 140 countries and 39 annual observations each. Therefore,
the time dimension reduces to eight observations: 1960–64, 1965–69, 1970–74, 1975–79,
1980–84, 1985–89, 1990–94, and 1995–98 (the last observation is an average over four
observations only). 9 Potentially the dimension of the panel would be 140 x 8=1120
observations. However, because of missing observations, the dimension of the unbalanced
panel is smaller.
If the threshold were known, the model could be estimated by ordinary least squares (OLS).
Since π* is unknown, it has to be estimated along with the other regression parameters. The
appropriate estimation method in this case is nonlinear least squares (NLLS). Furthermore,
since π* enters the regression in a nonlinear and non-differentiable manner, conventional
9 The initial income variable ly0 is computed as the five-year average of real income per capita in PPP terms for the previous five-year period, allowing the identification of ly0 under fixed effects.
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gradient search techniques to implement NLLS are inappropriate. Instead, estimation has
been carried out with method called conditional least squares which can be described as
follows. For any π* , the model is estimated by OLS, yielding the sum of squared residuals as
a function of π*. The least squares estimate of π* is found by selecting the value of π* which
minimizes the sum of squared residuals. Stacking the observation in vectors yields the
following compact notation for equation (1):
eXYd += πβ)log( , πππ ,...,= (2)
where βπ=(µi µt γ1 γ2 θ’)’ is the vector of parameters and X is the corresponding matrix of
observations on the explanatory variables. Note that the coefficient vector β is indexed by π
to show its dependence on the threshold level of inflation, the range of which is given by
π and π . Define S1(π) as the residual sum of squares with the threshold level of inflation
fixed at π. The threshold estimate level π* is chosen so as to minimize S1(π), that is:
},, ),{argmin* 1 ππππππ
…== (S (3)
It is important to determine whether the threshold effect is statistically significant. In
equation (1), to test for no threshold effects amounts simply to testing the null hypothesis
Ho: γ1 = γ2. Under the null hypothesis, the threshold π* is not identified, so classical tests,
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such as the t-test, have nonstandard distributions. Hansen (1996, 1999) suggests a bootstrap
method to simulate the asymptotic distribution of the following likelihood ratio test of H0 :
2
100 ˆ/)( σSSLR −= (4)
where S0, and S1 are the residual sum of squares under H0 : γ1 = γ2, and H1: γ1 ≠ γ2,
respectively; and 2σ̂ is the residual variance under H1. In other words, S0 and S1 are the
residual sum of squares for equation (1) without and with threshold effects, respectively. The
asymptotic distribution of LR0 is nonstandard and strictly dominates the 2χ distribution. The
distribution of LR0 depends in general on the moments of the sample; thus critical values
cannot be tabulated. Hansen (1999) shows how to bootstrap the distribution of LR0.
To proceed one can test for the existence of a threshold effect in the relationship between real
GDP growth and inflation using the likelihood ratio, LR0, discussed above. This involves
estimating equation (1) and computing the residual sum of squares (RSS) for threshold levels
of inflation ranging from π to π . The threshold estimate is the one that minimizes the
sequence of RSSs. The test for the existence of threshold effects has been conducted using
the full sample and two subsamples (industrial and developing countries). The results are
summarized in Table 1.
The first column gives the range over which the search for the threshold effect is conducted.
For the full sample, π =1 percent, π =100 percent, and the increment is 1 percent, which
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yields 100 panel regressions of equation (1).10 The minimization of the vector of 100 RSSs
occurs at the inflation level of 11 percent. Repeating the same procedure for the subsamples
yields a threshold estimate of 11 percent for developing countries and 1 percent for industrial
countries. An important result is that the threshold level for industrial countries is much
lower than that for developing countries. The column LR0 in Table 1 gives the observed value
of the likelihood ratio. The significance levels have been computed using the bootstrap
distributions (corresponding to the three samples) of LR0. The null hypothesis of no threshold
effects can be rejected at least at the 1 percent significance level for all three samples. Thus
the data strongly support the existence of threshold effects.
Two basic conclusions can be drawn from this set of statistical tests. First, the threshold is
around an inflation rate of 1 percent for industrial economies and 11 percent for developing
countries. Second, these threshold estimates are very precise. One needs to ask why the
threshold level for developing countries is higher than the threshold level for industrial
countries. There are at least two possible conjectures that we can make. First, the long history
of inflation in many developing countries led them to adopt widespread indexation systems
to negate, at least partially, the adverse effects of inflation. Once in place, these indexation
mechanisms make it possible for governments in these countries to run higher rates of
inflation without experienc ing adverse growth effects (because relative prices do not change
that much). Second, to the extent that inflation is viewed as a tax on financial intermediation,
governments, faced with a target level of expenditure will, in the absence of conventional 10 For industrial countries the upper bound has been set to 30 percent.
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taxes, levy the inflation tax. Accordingly, the differential threshold levels for the effects of
inflation on growth for industrial and developing countries could reflect the higher level of
conventional taxation in the former than in the latter. Thus, while relatively small increases in
inflation in industrial countries adversely affect investment (by raising the effective cost of
capital goods), productivity, and growth, in developing countries, with relatively low levels
of conventional taxes, a larger inflation tax is required to have the same growth-inhibiting
effects.11
Figure 1 shows the sensitivity of the effect of inflation on growth when the threshold level
varies from 1 percent to 50 percent. The three panels (corresponding to the three samples)
depict the effect of inflation on growth for economies with an inflation rate below the
threshold level (solid line) and for economies with inflation rates above the threshold level
(dotted line). The vertical line indicates the threshold estimate. The following points emerge
from Figure 1: (i) the high- and low-inflation effects are most sensitive to the location of the
threshold over the 1 to 20 percent range; (ii) the positive effect of inflation on growth is only
present for inflation rates lower than 5 percent for industrial countries and 18 percent for
developing countries; (iii) for developing countries, the inflation effect on growth, which is
negative over the whole range, strengthens as the threshold increases, which implies a
worsening of the negative effect of inflation on growth as inflation increases; and (iv) for
industrial countries, the inflation effect, while remaining negative over the entire range, first
11 Roubini and Sala-i-Martin (1995) and Cukierman, Edwards, and Tabellini (1992) have developed models that yield results along these lines.
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weakens (in absolute value) as the inflation threshold increases, reaches a minimum around a
threshold of 15 percent, and strengthens thereafter.
Having established that as inflation moves higher it exerts a negative effect on economic
growth, we now move to the relationship between inflation and financial deepening.
III. INFLATION AND FINANCIAL DEEPENING
As mentioned in the Introduction, it is empirically well-established that there are very strong
correlations between various measures of an economy’s financial depth and its long-run real
activity, as reflected in its long-run rate of growth. This is true both for measures of banking
activity, and for measures of stock market development. King and Levine (1993a,b) and
Beck, Levine, and Loyaza (2000), for example, demonstrate that measures of both bank
lending to the private sector, and measures of bank liabilities outstanding, are strongly
positively correlated with an economy’s level of real production, and with its real rate of
growth. Indeed, King and Levine (1993a,b) find that measures of banking activity are the
only “robustly significant” predictors of future growth performance. Similarly, Levine and
Zervos (1998) show that measures of stock market development are strongly associated with
both higher levels of real activity and higher real growth rates. While the direction of
causation is difficult to establish, Beck, Levine, and Loyaza (2000) find evidence that
causality runs from financial development to real development. Finally, Khan and Senhadji
(2000), in the most recent study of this subject, find that the effect of financial development
on growth is positive, and that the size of the effect varies with different measures of
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financial development, estimation method, data frequency, and the functional form of the
relationship.
In addition, there are a number of well-understood theoretical mechanisms by which
financial development promotes growth. The earliest contributions (Greenwood and
Jovanovic, 1990; Bencivenga and Smith, 1991) show how information acquisition by the
financial system promotes the efficient allocation of investment capital, and how bank
liquidity provision can alter the social composition of savings in a way that promotes both
physical and human capital accumulation. Subsequent contributions (Huybens and Smith,
1999) demonstrate that secondary capital (equity) markets should also be expected to
contribute to the growth process. It is well known that technological developments alone are
inadequate to promote growth. Agents are willing to tie up resources in new technologies
requiring large scale investments only if the capital markets exist that make these
investments sufficiently liquid.
If inflation affects the development of the financial system, it will almost necessarily have
long-run real effects. Moreover, as discussed in Section II, there is now considerable
evidence that there are thresholds in the empirical relationship between inflation and real
growth. The theories reviewed by Khan, Senhadji, and Smith (2001) deliver the prediction
that there are thresholds in the theoretical relationship between inflation and financial
activity, and that this may explain the threshold in the relationship between inflation and real
activity.
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The common theme in all of the theoretical literature is that financial market institutions arise
to address endogenous frictions that are present in the process of allocating credit and
investment capital. Indeed, such frictions seem essential in understanding the role of financial
institutions in development: in the absence of such frictions the Modigliani-Miller Theorem
would obtain, and the nature of finance would be irrelevant for allocations. Moreover, the
severity of financial market frictions is itself endogenous in the models we describe. Inflation
matters because it affects the severity of these frictions.
Suppose that higher rates of inflation are associated with lower long-run real rates of return
on a broad class of assets. Then increases in inflation will be associated with more severe
rationing of credit, reductions in financial depth, and lower levels of real activity. But why
should higher rates of inflation reduce long-run real returns? The answer is that, in any
economy, some agents hold real money balances either voluntarily or involuntarily. For
instance, the banking systems in every economy hold a significant quantity of non-interest-
bearing cash reserves. As is well-understood, higher rates of inflation act like a tax on real
balances or bank reserves. And, if this tax is borne, at least in part, by bank depositors, higher
inflation must lead to lower real returns on bank deposits. Since bank deposits compete with
a variety of assets, it is plausible that reduced real returns on bank deposits will result in
reduced real returns on a variety of assets. Barnes, Boyd and Smith (1999) and Boyd, Levine,
and Smith (2000) establish that this is, in fact, true for all but the highest inflation economies.
Moreover, Barnes, Boyd, and Smith (1999) also show that higher rates of inflation are
associated with lower real returns on short-term assets, government debt, and high grade
bank loans.
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Of course the mechanism just described explains why higher rates of inflation might reduce
financial depth, with corresponding adverse consequences for growth. It does not yet explain
why there might be threshold effects associated with the rate of inflation exceeding some
critical level. In order to understand how threshold effects might arise, suppose that, if the
rate of inflation is sufficiently low—and if real rates of return on savings are sufficiently
high—the adverse selection problem in credit markets does not bind. Or, in other words, if
real returns are high enough, credit rationing is not required to induce lenders to lend rather
than borrow. If this transpires, then at low enough rates of inflation the credit market operates
in a totally Walrasian way. Then, in a model that generates a Mundell-Tobin effect in the
absence of credit rationing, the following can occur. If the initial rate of inflation is
sufficiently low, and real rates of return are sufficiently high, an increase in the rate of
inflation causes agents to substitute away from cash and into investments in physical and/or
human capital. As a result, long-run growth is stimulated. However, if the rate of inflation is
increased excessively, real returns will be driven down to the point where credit market
frictions become binding. Once the rate of inflation exceeds this threshold level, further
increases in inflation will lead to credit rationing and have negative consequences for the
financial system and for growth. Thus there is a critical rate of inflation. Below this rate
modest increases in inflation can stimulate real activity and promote financial depth. Above
this threshold increases in the rate of inflation interfere with the efficient allocation of
investment capital, and consequently have negative growth consequences.
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While, as discussed above, there has been considerable theoretical analysis of the inflation
and financial depth link, empirical evidence is remarkably scarce. Indeed, the first empirical
study specifically on this is by Boyd, Levine, and Smith (2000) who examine time-averaged
data on bank credit extension to the private sector, the volume of bank liabilities outstanding,
stock market capitalization and trading volume (all as ratios to GDP), and inflation for a
cross-country sample. The empirical model they specify relates the various measures of
financial depth to inflation and a set of control variables. The authors find that, at low-to-
moderate rates of inflation, increases in the rate of inflation lead to markedly lower volumes
of bank lending to the private sector, lower levels of bank liabilities outstanding, and
significantly reduced levels of stock market capitalization and trading volume. They also find
that the relationship between inflation and financial market development becomes “flatter” as
inflation increases: that is, a given percentage point increase in the rate of inflation has a
much larger effect on financial development at low than at high rates of inflation. In addition,
they obtain similar results using non-overlapping panels of data averaged over five-year
intervals.
However, Boyd, Levine, and Smith (2000) do not explicitly test for the presence of threshold
effects in the inflation-financial depth relationship. Nor do their results easily permit a
comparison with the empirical findings on the links between long-run inflation and long-run
growth. To test for the existence of a threshold effect, Khan, Senhadji, and Smith (2001),
drawing upon the work described in Section II, utilized the following empirical model:
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ititititititit eXddfd ++−+−−= ')/1/1()/1/1)(1( *2
*1
**
θππγππγ ππ (5)
≤>
=*
*
01*
πππππ
it
itit if
ifd i=1,…,N; t=1,…,T
where fdit is an indicator of financial depth, πit is inflation based on the CPI index, π* is the
threshold level of inflation, and *π
itd is a dummy variable that takes a value of one for
inflation levels greater than π* percent and zero otherwise. Xit is a vector of control variables
which includes the log of income per capita (log(pppgdp)), the degree of openness (open),
the share of public consumption in GDP (cg), a time trend (trend) and three regional
dummies, a dummy for Latin American countries (d_la), a dummy variable for Asian
countries (d_as), and a dummy variable for advanced countries (d_adv).12 The subtraction of
1/π* from 1/πit in equation (1) makes the relationship between financial depth and inflation
continuous at the threshold level π*.13 The first term in equation (1) gives the effect of
inflation for inflation rates below or equal to the threshold. Similarly, the second term
measures the effect of inflation on financial development for inflation rates above the
threshold level.14
12 Because the estimation method requires a large sample, individual equations for these (and other) group of countries cannot be estimated precisely.
13 Continuity of the relationship given in equation (1) is desirable, otherwise small changes in the inflation rate around the threshold level will yield different impacts on financial depth depending on whether inflation is increasing or decreasing.
14 Theoretically, the relationship between financial depth and inf lation may be characterized by multiple thresholds. However, as it is very difficult to estimate multiple thresholds, equation (1) only considers the single-threshold case.
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The dataset utilized in this paper includes 168 countries (comprising both industrial and
developing countries) and generally covers the period 1960–99. Data for a number of
developing countries, however, have a shorter span. Because of the uneven coverage, the
analysis is conducted using unbalanced panels. The data come primarily from a new financial
development dataset developed by Beck, Demirgüç-Kunt, and Levine (1999) and the
International Financial Statistics of the International Monetary Fund. Financial depth is
measured by several alternative indicators: (i) fd1: defined as domestic credit to the private
sector as a share of GDP; (ii) fd2: defined as fd1 plus stock market capitalization as a share of
GDP; and (iii) fd3: defined as fd2 plus private and public bond market capitalization as a share
of GDP. By definition, fd3 is the most exhaustive indicator of financial depth, but is only
available for advanced countries and for a shorter time span (starting 1975). By contrast, fd1
is widely available, but is a more limited proxy for financial depth.
We can proceed to test for the existence of a threshold effect in the relationship between
inflation and financial depth using the likelihood ratio, LR0, as discussed in Section II. This
implies estimating equation ( 5) and computing the residual sum of squares (RSS) for
threshold levels of inflation ranging from π to π . Recall that the threshold estimate is the
one that minimizes the sequence of RSSs. The test for the existence of threshold effects has
been conducted using the three selected indicators of financial depth. The results are
summarized in Table 2.
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The first column gives the range over which the search for the threshold effect is conducted,
which is 1 percent to 100 percent with increments of 1 percent. This yields 100 panel
regressions of equation (5). Using fd1 as an indicator of financial depth, the minimization of
the vector of 100 RSSs occurs at the inflation level of 6 percent. Repeating the same
procedure for fd2, and fd3 yields threshold estimates of 3 percent and 5 percent, respectively.
The column LR0 in Table 1 gives the observed value of the likelihood ratio. The significance
levels have been computed using the bootstrap distributions (corresponding to the three
indicators of financial depth) of LR0. The null hypothesis of no threshold effects can be
rejected at least at the 1 percent significance level for all three indicators of financial depth.
Thus the data strongly support the existence of threshold effects.
In Figure 2, for each measure of financial depth, the three panels show the effect of inflation
on financial depth as inflation increases from 1 percent to 100 percent. All three indicators of
financial depth yield a similar pattern for the effect of inflation on financial depth. Below the
threshold, an increase in inflation has a small positive but statistically insignificant effect on
financial depth (except for fd1, which shows a small negative but statistically insignificant
effect). Above the threshold, increasing inflation significantly hampers financial depth. And, it
bears emphasizing that the adverse effects of inflation for the financial system are particularly
strong for economies with modest rates of inflation (but ones that exceed the threshold).
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IV. CONCLUSIONS
The recent empirical growth literature has consistently found a negative but nonlinear
relationship between inflation and growth. The nonlinearity in the relationship arises from
the existence of threshold effects, that is, there is a threshold level of inflation below which
inflation has no significant effect on growth, but beyond which inflation significantly
hampers growth. Recent theoretical models provide some interesting insights about this
relationship, arguing that the main mechanism of transmission can be through financial
markets. In the presence of frictions (arising from, for example, adverse selection, moral
hazard, or costly state verification), inflation impedes financial development, and thus
growth, by affecting the severity of these frictions. In particular, higher inflation leads to
increased credit rationing and reduced extension of bank credit and therefore to lower
investment and slower growth. These theoretical models further predict a nonlinear
relationship between inflation and financial development, and thus between inflation and
growth, that is similar to that uncovered in empirical work.
The empirical results reported in this paper strongly support the notion of nonlinear
relationships between inflation and growth, and between inflation and financial deepening.
Inflation starts to exert a negative effect on growth as low as at around 1 percent in industrial
countries and at about 11 percent in developing countries. The threshold level of inflation
beyond which inflation significantly hinders financial deepening is estimated to be in the
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3-6 percent range. When combined, these results provide strong support for the view taken in
this paper that financial markets are an important channel through which inflation affects
growth in a nonlinear fashion.
In conclusion, policymakers around the world during the last decade or so have recognized
that low inflation is conducive to the development of financial systems and markets and to
strong growth performance. The goal has been to bring inflation down to single digits and to
keep it there. The results contained in this paper provide strong empirical confirmation of this
strategy. Once the rate of inflation starts to cross the 5-10 percent mark, it will begin to exert
a negative effect on financial deepening, and through this channel, have an adverse effect on
economic growth. Low inflation, financial development, and higher growth appear to go
hand in hand.
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Table 1. Test Results of Threshold Effects
Sample
Search Range for Thresholds
Threshold Estimate (%)
LR0
Critical
Values (%)
Significance Levels
All Countries {1, 2,3,…,100} 11 10.59 7.47 0.001
Industrial Countries {1, 2,3,…,30} 1 8.80 6.63 0.005
Developing Countries {1, 2,3,…,100} 11 10.89 6.21 0.000
Table 2. Test Results of Threshold Effects
Dependent variable
Search Range for Thresholds
Threshold Estimate (%)
LR0 Critical Values (1%)
Significance Levels
fd1 {1, 2,3,…,100} 6 246.9 5.93 0.000
fd2 {1, 2,3,…,100} 3 50.20 14.49 0.000
fd3 {1, 2,3,…,100} 5 34.38 13.00 0.000
Note: The second column gives the range over which the search for the threshold effect is conducted, the third column gives the threshold estimate in percent, the column LR0 gives the observed value of the likelihood ratio, the fifth column gives the critical values, and the last column gives the corresponding significance level, both computed using the bootstrap distributions (corresponding to the three samples) of LR0.
For a more detailed discussion on the computation of the bootstrap distribution of LR0, see Hansen (1999).
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Figure 1. Sensitivity of the Effect of Inflation on Growth to the Threshold Level
Note: The low (solid line) and high (dotted line) effects are respectively given by the coefficients of equation (1). The threshold varies from 1 to 50 percent, except for industrial countries where the range is from 1 to 30 percent. The vertical line indicates the estimate of the inflation threshold.
-0.02
0.00
0.02
0.04
0.06
0.08
5 10 15 20 25 30
Industrial Countries
-0.010
-0.008
-0.006
-0.004
-0.002
0.000
0.002
5 10 15 20 25 30 35 40 45 50
Developing Countries
-0.010
-0.008
-0.006
-0.004
-0.002
0.000
0.002
5 10 15 20 25 30 35 40 45 50
Full Sample
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Figure 2. Effect of Inflation on Financial Depth
Note: This figure shows the effect of inflation on financial depth (for inflation rates from 1 to 100 percent) using the coefficient estimates of equation (5). Both inflation and financial depth are expressed in percentage terms.
fd1
fd2
fd3
-20
-15
-10
-5
0
5
20 40 60 80 100
Inflation
-50
-40
-30
-20
-10
0
20 40 60 80 100
Inflation
-120
-100
-80
-60
-40
-20
0
20 40 60 80 100
Inflation
- 24 -
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