MEASURING UNCERTAINTY IN THE FINANCIAL
SECTOR
AYTAÇ ERDOĞAN
Statistics Department
EU Workshop on Recent Developments in Business and Consumer Surveys
November 13-14, 2014
Brussels, Belgium
* Corresponding author. aytac.erdogan@tcmb.gov.tr
Outline
 What is Uncertainty?
 Aim of the Paper
 Summary of Literature About Measuring Uncertainty
 Financial Services Survey
 Methodology
 Results
 Conclusion
What is Uncertainty?
At a general level, uncertainty is defined as
the conditional volatility of a disturbance that is
unforecastable from the perspective of economic agents.
 A key concern for agents in the economy
 Higher uncertainty has adverse effects
 In spite of its importance, measuring uncertainty is a real
challenge for statisticians.
Aim of the Paper
 Lack of a proper measure of uncertainty about financial
services
 This study proposes a (proxy) measure, using expectation
errors of managers in the financial sector
 The identifying assumption is that higher uncertainty is
closely related with higher expectation errors.
 Relatively new survey, only visual evidence is found
Summary of Literature
What is the impact of time-varying business uncertainty on economic activity

Guiso and Parigi (1999)

Bloom, Bond and van Reenen (2007)

Bloom, Floetotto and Jaimovich (2009)
Summary of Literature
Our work is closely following
 Bachmann, Elstner and Sims (2010) and Arslan et al. (2011) construct measures of
time-varying uncertainty from business surveys.
 They examine their relationship with economic activity over the business cycle for
German and Turkish data.
 Both studies use forecast errors of participants as a proxy for uncertainty,
stemming from the identifying assumption that higher uncertainty causes higher
forecasts errors.
 They both show that uncertainty has a strong relationship with output and can be
used as a leading indicator
 Unlike them, we measure uncertainty in the financial sector by using Financial
Services Survey data.
Financial Services Survey
 Financial Services Survey (FSS) is one of the surveys of “The Joint Harmonized EU
Programme of Business and Consumer Surveys.
 In Turkey, FSS was started in May 2012 and is fully harmonized with the EU
programme.
 In Turkey, FSS covers 6 sectors
Sector
Number for Institutions
Sector Share (%)
Coverage (%)
Banking
49
92.5
100.0
Insurance
20
3.3
85.6
Financial Leasing
11
1.6
88.3
Factoring
28
1.1
85.2
Financing
5
0.8
84.8
20
0.7
87.2
Brokerage
Survey Questions
•
The questionnaire consists of two question forms
•
The first form comprises five questions are asked at a monthly frequency. They
refer to :
Past development of the business situation
 Past and expected demand developments
 Past and expected employment developments

•
The second form of fourteen questions is part of the quarterly questionnaire and
is used in January, April, July and October.
•
They refer to past and future assessments of :





Operating income
Operating expenses
Profitability
Capital expenditure
Competitive position
Financial Services Survey
 There are three different answer categories: increase/improve, remained unchanged, and
decrease/deteriorate.
 In particular, response (in the time 𝑡 survey) to the question which asks expectations
regarding the demand for services (turnover) in the next three-month period is compared
with response (in the time 𝑡 + 3 survey) to the question which asks about realizations in the
past three-month.
• Therefore, answers to expectation questions (at time t) and realization questions (at time
t+3) will cover the same period. This property allows us to analyze expectation errors.
Development over the last 3 months (t+3)
𝜖𝑖𝑡
Increased
months (t)
Decreased
Increase
0
-1
-2
Remain unchanged
1
0
-1
Decrease
2
1
0
Expectations
over the next 3
Remained unchanged
Methodology
Total uncertainty is the sum of weighted squared institutionspecific errors:
𝑈𝑡 =
𝑁
2
𝑤
𝜖
𝑖=1 𝑖𝑡 𝑖𝑡 ,
and
𝑁
𝑖=1 𝑤𝑖𝑡
=1
where 𝑤𝑖𝑡 is the weight of financial institution 𝑖,
Methodology
 Increase in the uncertainty measure 𝑈𝑡 can stem from two different factors
 𝑈𝑡 = 𝐿2𝑡 + 𝐷𝑡 . (by identity)
 The aggregate effect, 𝐿𝑡 =

An increase (or a decrease) in the mean expectation results in higher 𝑈𝑡 . When an unpredictable
aggregate shock hits the economy most participants will face an error in their forecasts and hence
𝑈𝑡 will increase.
 The discrepancy. 𝐷𝑡 =

𝑁
𝑖=1 𝑤𝑖𝑡 𝜖𝑖𝑡 .
𝑁
𝑖=1 𝑤𝑖𝑡
𝜖𝑖𝑡 − 𝐿𝑡
2.
When participants make different errors, this means that there are idiosyncratic shocks. Therefore,
the discrepancy is defined by the weighted squared differences of expectation errors from the mean
errors
 Total uncertainty is the sum of (squared) aggregate factors and idiosyncratic
factors.
Results
 Fed announcement in May 2013
 Also starting late May, a wave of demonstrations against the government and civil unrest,
which is called Gezi protests, occurred and lasted a couple of months in Turkey.
 Under these circumstances, capital inflows to Turkey have also weakened and uncertainty
about what would happen in domestic financial markets increased significantly
 Our measure, 𝑈𝑡 , is also increased by eight times m-o-m and by almost 200 percent with
respect to early 2013 averages.
Results
 Domestic political risk increased substantially due to corruption claims against the
government in October and November 2013.
 𝑈𝑡 increased by 40 percent
 Local elections in late March amid corruption claims and increased political uncertainty.
 𝑈𝑡 reached its highest level in March 2014
Results
 In June 2014, war and terrorism fears in Ukraine and Iraq were the main driving force in
increased uncertainty. Turkey has significant economic relations with these neighbors and,
before June 2014, Iraq had become the biggest export market for Turkish goods. Increased
violence weighed heavily on export figures and raised concerns about the future. Amid these
tensions, 𝑈_𝑡 has increased to its high levels again.
Results
 Discrepancy (idiosyncratic factors) is the main driving factor for total uncertainty (for Turkish
financial sector in the given period of time).
 Somewhat surprising


All events discussed are economy-wide
Nevertheless, the biggest hike that happened in February 2014 can be explained by idiosyncratic
factors as most polls diverged before the local elections and this could shape expectations of
institutions differently.
Methodology
 One question: Are these hikes represent level shocks rather than uncertainty
shocks?”
 That is, level effects, should be taken into consideration as well.
We compute balances:
𝐵𝑡 =
𝑁
𝑖=1 𝑤𝑖𝑡 𝑅𝑖𝑡 ,
𝑅𝑖𝑡 : the response given by participant 𝑖 at time 𝑡 and can take values 1, 0, −1, for will
increase, will remain unchanged and will decrease.
𝐵𝑡 is an indicator of, on average, how participants expect their future turnover.
Results
 Level effects move in line with uncertainty only for February 2014.
 Before the local elections, expectations deteriorated and this could be a complementary
factor in the rise of 𝑈𝑡 .
 Other times, increases in total uncertainty are not accompanied with adverse level shocks.
 For example, expectations remained stable in May 2013 when Fed announcement on its
asset-purchasing programme increased 𝑈𝑡 significantly.
 Level shocks are important but they are not necessarily the main factor in 𝑈𝑡 developments
Conclusion
1. Uncertainty measure derived from forecast errors can be used as a good proxy for
uncertainty
 Big hikes at times when most important recent events in Turkish and
international financial sector.
 Robust when controlled for level effects
2. Discrepancy is the main driving factor for total uncertainty
 Only visual evidence due to lack of a long time series.
 A more proper empirical research is forthcoming
CENTRAL BANK OF THE REPUBLIC OF TURKEY
aytac.erdogan@tcmb.gov.tr