REFILL, PLEASE?

#2

REFILL, PLEASE?

Consumer savings are running out. Can fiscal and pre-election spending refill it?

July 2023

Barra Kukuh Mamia Senior Economist

Executive Summary

• Excess savings carried over from the pandemic have fueled consumption recovery in the past year, especially as household saving rates declined.

• These savings are dwindling and will likely run out in H2-23, while spillover from corporate savings are limited by the weak appetite to expand or recruit.

• Consumer loans, as an alternative liquidity source for households, are also slowing down despite regulatory support and a relative lack of transmission in terms of interest rate hikes.

• Declining liquidity translates to a slowdown in consumption and retail investment – but, interestingly, not consumer confidence.

• Part of the recent decline in household liquidity can be attributed to the fiscal cycle – which means the flow of funds could reverse (i.e. going from the government to the households and private sector) in H2-23.

• But while in theory the government has nearly IDR 1,000 Tn (net) to spend, it may not be able to ramp up spending in time.

• Pre-election spending could also boost growth to a small extent (around 0.1% YoY) amid this compressed electoral cycle.

• Both the fiscal cycle and pre-election spending could yet push this year’s GDP growth towards 5.0%, albeit narrowly, amidst growing

global headwinds.

Another data dive, this time on consumers’ outlook

Where are we going now?

• As we hinted in the intro to the firstCollideascope, this is a report that can go anywhere and everywhere, so long as it (a) is relevant to the Indonesian economy, and (b) presents an opportunity for us to explore, analyze, and visualize data in interesting ways.

• For this edition, we were inspired by recent discussions about ex- cess savings in the US. This legacy of the pandemic is seen as one reason why the US has yet to enter recession – and also a culprit behind the persistence of inflation prior to the recent drop-off.

• For Indonesia, there are no equivalent dataset to calculate excess savings, but we have a decent proxy: individual deposits from BI’s Economic and Financial Statistics (SEKI).

• The resulting estimates are similar enough to the US, with excess savings projected to run out at some point in H2-23 (pg. 5), and the post-pandemic consumption boom partly being financed by a one-time drop in saving rates(pg. 9). As these effects fade, con- sumption may slow accordingly, especially when coupled with a decline in consumer loan growth(pg. 12-14).

Why this topic?

• There is however one major difference between consumer excess savings in the US and Indonesia: the latter shows sharp seasonal fluctuations attributable to the annual fiscal cycle(pg. 15). This is actually a long-running problem (pg. 18-19) – but it becomes a key issue this year as tax receipts exceed expectations(pg. 16-17).

• As much as the fiscal cycle hinder consumption in the first half of the year, however, it should also boost it in the second half. The other politics-related cycle – the election cycle – can also add to growth, albeit more narrowly than some would prefer(pg. 20-23).

With global momentum clearly weakening, optimizing these two cycles is crucial if we are to achieve 5%-plus growth this year.

• Finally, we have a little Easter egg at the end of this report(pg.

24-25), which is tangentially related to the two main topics here:

consumer behavior and government/politics. It is by no means a rigorous or in-depth analysis, but it does give an interesting over- view of the priorities of Indonesian voters.

0 1000 2000 3000 4000 5000 6000 7000

Jan-15 Jan-16 Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

-500 0 500 1000 1500 2000 2500

Jan-20 Jan-21 Jan-22 Jan-23

US consumers are still burning through their excess savings …

Massive pandemic-era savings gave way to dis-savings … … but the residuals could support demand into Q4-23

Source: St. Louis Fed, calculations by BCA Economist Source: St. Louis Fed, calculations by BCA Economist

• Much of the excess savings came from fiscal stimulus packages enacted under Pres. Trump (CARES Act, Mar-20) and Pres. Biden (American Rescue Plan, Mar-21).

• Consumer dis-saving since mid-21 is partly fueled by inflation, which US consumers have compensated for by ramping up nominal spending – whereas real spending growth are merely back to pre-pandemic trends.

― US personal savings (annualized)

-- 2016-19 trendline

910.3

US personal excess savings

(cumulative)

457

latest (May-23)

Oct-23

2162 peak (Aug-21)

USD Bn USD Bn

CARES Act ARP

-20 0 20 40 60 80 100 120

Jan-20 Jan-21 Jan-22 Jan-23

0 50 100 150 200 250 300 350

… as are Indonesian consumers, but possibly at faster rates (!)

― ID chg in individual deposits (YoY)

-- 2016-19 average

136.6

ID individual

excess savings

(cumulative, smoothed) 110.8

21.6

peak (Aug-21)

Deposit growth by individuals are close to historic lows … … which implies rapid burn-through of excess savings

IDR Tn IDR Tn

Source: BI, calculations by BCA Economist Source: BI, calculations by BCA Economist

• BI’s bank deposit data by individuals provide a decent parallel to US personal savings – and indeed they show a similar pattern since 2020.

• Indonesia experiences lower inflation than the US recently, implying faster real consumption growth. But Indonesian households are also draining their savings at faster nominal rates, especially between May-Aug ’22 and again between Feb-Apr ’23. This trend was briefly halted during Q4-22, which crucially coincided with a massive burst of government spending(more on this later).

latest (May-23)

Sep-23

savings rebounded in

Sep-Dec ‘22

0 100 200 300 400 500 600 700 800

Jan-20 Jan-21 Jan-22 Jan-23

0 100 200 300 400 500 600

High corporate savings are not “trickling down” to consumers

― ID chg in private corporate deposits (YoY)

-- 2016-19 average

244.5

702.8

IDR Tn IDR Tn

Corporate savings were boosted by commodity windfall … … but they are still rising even after prices normalized

• Corporates are not normally net savers in the banking system – but since the pandemic, their savings have exceeded their net borrowing.

• These savings were partly driven by the commodity boom, but they are also indicative of weak business spending – indeed, savings are still growing albeit more weakly in spite of recent decline in commodity prices. This implies limited appetite for expansion and new recruitment, which could limit how much of these corporate savings could trickle down to consumers.

ID private corporate excess savings

(cumulative, smoothed)

Source: BI, calculations by BCA Economist Source: BI, calculations by BCA Economist

commodity boom

-100 -50 0 50 100 150 200 250 300 350

-100 -50 0 50 100 150 200 250 300 350 400

Dwindling consumer savings mostly go to FX and time deposits …

Recent deposit growth has been concentrated in FX … … while among IDR deposits, TD predominates vs. CASA

Source: BI, calculations by BCA Economist Source: BI, calculations by BCA Economist

IDR Tn (YoY) IDR Tn (YoY)

122.4 14.2

95.2 27.2

Chg in individual IDR deposits

Chg in individual FX deposits

Chg in individual IDR CASA

(checking + saving accounts)

Chg in individual IDR TD

(time deposits)

• The shift towards FX and TD are can largely be explained by recent IDR appreciation and interest rate hikes, respectively.

• However, since FX and TD are less liquid than cash or savings account (SA), this could also indicate less appetite to spend in the near-term.

Or, alternatively, those acquiring them may already have sufficient cash and SA at hand (i.e. upper- and middle-class households).

TD growth began to fall in Jan-21 …

… and rose again in Nov-22

-20 -10 0 10 20 30 40

Jan-20 Jul-20 Jan-21 Jul-21 Jan-22 Jul-22 Jan-23

0 10 20 30 40 50 60 70 80 90 100

-400 -300 -200 -100 0 100 200 300 400 500

Jan-20 Jul-20 Jan-21 Jul-21 Jan-22 Jul-22 Jan-23

… but not so much into bonds and equities

Retail bond purchase slows outside of primary issuance … … and the same can be seen for stocks since Q4-22

Source: MoF, calculations by BCA Economist Source: KSEI, IDX, calculations by BCA Economist

IDR Tn

-5.0

54.3 65.7

Monthly increase in equities ownership by domestic investors

Equity transaction frequency via brokerage firms 

Mn transactions

• Interestingly, households are showing less appetite from bonds and stocks – not to mention more speculative assets like cryptos, etc.

• Note that the big influx towards equities happened between Q1-21 and Q3-22, precisely when savers withdrew from TD due to low yields (see pg. 7). What we are seeing, then, is a “reflux” of that liquidity back towards TD – meaning that the apparent “savings” in recent months are partly the result of portfolio rebalancing among high-income households.

Monthly increase in gov’t bond ownership by individual investors

IDR Tn

* shaded area = primary issuance of retail gov’t bonds (ORI, SBR, SR, ST)

retail stocks purchase first peaked in

Jan-21 … … and fell

after Sep-22

12 14 16 18 20 22 24

-30 -20 -10 0 10 20 30 40

Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

Consumption recovery was financed by a decline in saving rates

% %

 Real retail sales index YoY Consumer saving rate 

8.0

saving rates not reported during Apr-Jul ‘20

Source: BI, calculations by BCA Economist

15.3

• The rapid depletion of consumer excess sav- ings is a concern, as it has been a key driver of the post-pandemic recovery.

• At the start of the pandemic, saving rates in- creased as consumers were unable to spend – while government social assistance by the government accrued to poorer households.

• But then mobility restrictions were relaxed (albeit intermittently tightened), and saving rates fell. Not coincidentally, this initial de- cline was associated with the first rebound in retail sales.

• Saving rates have increased somewhat since then, but it is still far lower than the ~20%

rates we saw prior to the pandemic.

• So it is as yet unclear if this “new normal” of low saving rates could be sustainable, or if things would revert to the old norm – which would necessitate a short-term decrease in consumption.

saving rates fell sharply in early 2021

-30 -20 -10 0 10 20 30 40

Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

Consumer confidence is decoupled from retail sales …

%

― Real retail sales index YoY

― Consumer confidence index

(percentage relative to neutral)

― BCA Spending Index (Intrabel*) YoY

(CPI-adjusted, 7M centered moving avg.)

8.0 28.3

4.2

Source: BI, BCA Big Data, calculations by BCA Economist * in Indonesian, IndeksTransaksiBelanja

• And indeed, there has been a decline in real retail sales growth more recently – although things seems to be improving in June, for a reason that we will discuss later(pg. 15-19).

• These fluctuations in retail sales seem to be confirmed by our Intrabel, or BCA Spending Index – which tracks the aggregate volume of retail purchase by individual BCA custom- ers.

• Consumer sentiment, meanwhile, seems to be far more optimistic. This may have some political import as we will see later(pg. 24), but psychological factors might also be in- volved here.

• Specifically, recency bias may lead consum- ers to think that things are back to normal, even though a closer look at BI’s retail data (pg. 11)would show this “new normal” are still some way off from the olden days, par- ticularly for durable goods.

0 20 40 60 80 100 120

Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

RSI: IT & Communication Eqs.

40 50 60 70 80 90 100 110 120 130 140

Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

RSI: Household Equipments

60 80 100 120 140 160 180

Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

RSI: Vehicle Parts & Accessories

0 20 40 60 80 100 120 140 160 180 200

Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

RSI: Clothing

0 20 40 60 80 100 120 140

Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

RSI: Cultural & Recreational

80 90 100 110 120 130 140 150 160

Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

RSI: Food, Beverages, & Tobacco

… which may reflect “scarring effect” from the pandemic

index (2017 = 100) index (2017 = 100) index (2017 = 100)

index (2017 = 100) index (2017 = 100) index (2017 = 100)

Source: BI, calculations by BCA Economist

--- pre-pandemic trendline

scarring effect

back to pre- pandemic trend

scarring effect

back to pre-pandemic (negative) trend

widening gap widening gap

-50 0 50 100 150 200 250 300 350 400

-400 -300 -200 -100 0 100 200 300 400

Consumer loans are beginning to plateau …

Individual net borrowing have slowed in 2023 … … even if we exclude SME loans which began to fall earlier

Source: BI, calculations by BCA Economist Source: BI, OJK, calculations by BCA Economist

IDR Tn (YoY) IDR Tn (YoY)

Chg in individual net liquidity:

Deposits Loans (negative contrib.)

-142.5 136.6

-279.1

Chg in individual loans:

Consumer loans

SME loans

87.1 279.1

144.0

• Even with low saving rates and declining excess savings, there is another way to finance consumption, i.e. by borrowing. We can track these bank loans by individuals using the same dataset from BI where we obtain individual and corporate deposits data(pg. 5-6).

• As it turns out, this data series include consumer loans as well as SME loans – which is often made on behalf of an individual rather than a firm. Still, if we exclude these loans, we can see quite clearly that consumer loans have been slowing in recent months.

• If we divide these consumer loans by type – and add loans made via non-bank financing companies (also known as multifinance) – it is evident that this slowdown is not uniform.

• Motor vehicle and credit card loans are still growing at double-digit rates. Partly, this is a rebound from the pandemic, when both of these categories saw negative growth.

• The situation also varies for property loans.

Demand for landed houses remains stable, but apartment – which boomed before the pandemic – seems to be headed for a bust.

• It is notable that consumer loans are still be- nefiting from regulatory support, especially BI’s relaxation of loan-to-value (LTV) ratios.

• The average rate on consumer loans is also unchanged from mid-2022 – showing banks’

reluctance to pass on BI rate hikes. All these means that the slowdown is probably driven

by demand more than supply factors. ^-40

-30 -20 -10 0 10 20 30

Jan-16 Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

… although certain types of lending are still holding up

-1.0 16.3 11.6

Consumer loans

(bank & multifinance), by type:

― Landed house ― Apartment

― Shophouse ― Household appliance

― Motor vehicle ― Credit card

6.84.8

YoY %

Source: OJK, calculations by BCA Economist

9.4

0 2 4 6 8 10 12 14

Jan-19 Jul-19 Jan-20 Jul-20 Jan-21 Jul-21 Jan-22 Jul-22 Jan-23

Even fintech loans have started to dry up

Fintech lending abruptly slowed at the turn of the year … … as credit risk has gradually been creeping up

0 10 20 30 40 50 60

Jan-19 Jul-19 Jan-20 Jul-20 Jan-21 Jul-21 Jan-22 Jul-22 Jan-23

Source: OJK, calculations by BCA Economist Source: OJK, calculations by BCA Economist

IDR Tn %

Loans by fintech, by borrower type:

Individuals

Businesses

Nonperforming fintech loans, by length of non-payment:

current methodology started in Jan-21

30 – 90 days

> 90 days

51.5

5.8

45.6

7.5

3.8

• But are borrowers just switching from the traditional lenders to a newer type of lenders, i.e. fintech? The answer is partly yes, in 2021-22, but certainly no, in 2023.

• Unlike banks, the slowdown in fintech might be attributed as much on the supply-side as on the demand. Relative decline in liquidity being injected/channeled to these companies may be forcing them to be more restrictive in issuing new loans.

0 200 400 600 800 1000 1200 1400 1600

Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18 Dec-19 Dec-20 Dec-21 Dec-22

Liquidity in government accounts is nearing all-time highs

Source: BI, calculations by BCA Economist

IDR Tn

211 1,249

309

730

Dec

Government deposits:

 Central government at Bank Indonesia

 Central government at commercial banks

 Regional government at commercial banks

Dec Dec Dec Dec Dec Dec Dec Dec Dec Dec Dec

Apr

Apr

Apr Apr Apr

• As mentioned(pg. 5), fiscal spending in Q4-22 helped to “top up” consumer savings. The fact that the opposite happened in Jan-Apr ’22 is likely related to the rapid decline in consumer savings at that time, while disbursement after April may account for the rebounds that we saw at the tail end of our dataset(pg. 5-10).

• Note also that government deposit at BI are not loanable, nor are they part of the broad money stock (M2) – with interesting implications.

Sep

-1000 -800 -600 -400 -200 0 200 400 600

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

The government still has room for IDR 1,000 Tn of net spend …

Gov’t budget balance:

― 2019 ― 2020

― 2021 ― 2022

― 2023

+391

-598

Source: Ministry of Finance, calculations by BCA Economist

IDR Tn

• The government’s overflowing coffers mean that there is a clear way out of the potential consumption slowdown – provided that the government spends its funds on time.

• Per May, the budget balance was nearly IDR 1,000 Tn above target. This is far larger than usual – the closest year being 2020, when there was an obvious urgency to spend.

• The MoF’s recent announcement – that the deficit could be about 20% smaller – seems like an acknowledgement of the difficulties in ramping up spending.

• There is also the question of timing. Excess savings might dry up by Q3, but the histo- rical pattern(pg. 15)suggests that a belated rush in Q4 is the likelier outcome.

• To be fair to the government, however, this year’s fiscal glut is not due to unusually slow spending, but rather a stronger-than-normal revenue, especially taxes(pg. 17).

... partly due to this year’s particularly strong tax receipts

Source: MoF, calculations by BCA Economist

* 2020 target is based on revised Budget after the Covid-19 emergency was declared

46.9

0 20 40 60 80 100 120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tax revenue

59.0

0 20 40 60 80 100 120 140 160 180

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Non-tax revenue

31.8

0 20 40 60 80 100 120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Central gov’t spending

35.6

0 20 40 60 80 100 120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Regional transfers

Gov’t budget realization (% of target):

― 2019 ― 2020*

― 2021 ― 2022

― 2023

Source: Ministry of Finance, calculations by BCA Economist

IDR Tn IDR Tn

IDR Tn IDR Tn

The fiscal cycle has a marked effect on other sectors’ liquidity …

• Unfortunately, the timing mis- match between fiscal revenue and spending – which we may call the “fiscal cycle” – has big impact on the rest of the eco- nomy.

• Deposits held by both individu- als and private corporates has the opposite pattern – they fall early in the year before reco- vering in December.

• Interestingly, the negative cor- relation is far weaker for SOEs.

This may be reflect direct, mid- year cash injection by the go- vernment, especially related to subsidies.

y = -0.087x + 2.4301 R² = 0.1204

-60 -40 -20 0 20 40 60

-200 -100 0 100 200 300

Gov’t vs. SOE deposits

y = -0.2816x + 15.233 R² = 0.2506

-200 -150 -100 -50 0 50 100 150 200

-200 -100 0 100 200 300

Gov’t vs. private corp deposits

y = -0.369x + 19.755 R² = 0.3363

-150 -100 -50 0 50 100 150 200

-200 -100 0 100 200 300

Gov’t vs. individual deposits

Source: BI, calculations by BCA Economist IDR Tn

IDR Tn

IDR Tn

IDR Tn

IDR Tn

IDR Tn

(data from 2011-23)

X-axis: Chg in gov’t deposits (YoY) Y-axis: Chg in individual / SOE /

private corp deposits (YoY)

 Jan-Nov  December

… causing overall system liquidity to peak late in the year

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19 Jan-20 Jan-21 Jan-22 Jan-23

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Broad money (M2),

deviation from H-P filter trend

Average deviation per month:

― Whole sample (2000-23)

― 2011-19 only

Source: BI, calculations by BCA Economist

• Recall also that funds sequestered at BI are not part of M2. As a result, the money stock is about 2% higher in December, but hit a low during Feb-May.

• In theory, the private sector – particularly those reliant on fiscal spending like govern- ment subcontractors – could borrow from banks to tide over their liquidity needs. Alas, the sharp M2 fluctuations suggests that this does not fully smooth out the fiscal cycle.

• It may also explain some, but not all, of the seasonal flux in nominal GDP, which usually peaks in Q3(pg. 21).

• Weirdly, the peak of M2 in Q4 tends to be overpowered by a big trough in money velo- city. This suggests that the typical “belated rush” spending pattern may not be the most effective in supporting growth.

Earlier, briefer election cycle = Earlier, briefer election effect?

Q1 Q2 Q3 Q4

2000 2001 2002

2003 t-3 t-2

2004 t-1 LE PE 1/2

2005 2006 2007

2008 t-3 t-2

2009 t-1 LE PE

Q1 Q2 Q3 Q4

2010 2011 2012

2013 t-3 t-2

2014 t-1 LE PE

2015 2016 2017

2018 t-3 t-2

2019 t-1 SLPE

Q1 Q2 Q3 Q4

2020 2021 2022

2023 t-3 t-2 t-1

2024 SLPE

Note:

LE = Legislative Election

PE = Presidential Election (1 or 2 rounds) SLPE = Simultaneous Legislative &

Presidential Elections

• Another thing that is also touted as a savior of growth in the second half of the year is the so-called “election effect”, whereby greater and/

or faster money circulation is expected to spur growth.

• We extended our simple decomposition exercise to all four variables in the quantity theory of money(pg. 21-22). It shows that the third quarter leading up to the Elections shows 0.4% increase in GDP growth, but this effect fades in subsequent quarters.

• The question, then, is if we are going to see this effect earlier, given the decision to conduct the Elections in February instead of April. We doubt this, as the political landscape is as yet still fluid – with coalition and President/VP candidates still not solidified – and the Elections Commission restricting campaigning until after Nov 28^th. This could imply a more compressed, but rather belated, election effect.

Q3

Q4

Q1 Q2 Q3

-1.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

t-3 t-2 t-1 t t+1

Broad Money

Election periods are associated with greater money velocity …

Average deviation from trend:

Q3

Q4

Q1

Q2

Q3

-4.0%

-2.0%

0.0%

2.0%

4.0%

t-3 t-2 t-1 t t+1

Velocity of Money

0.6%

0.5% 0.6%

0.5%

0.3%

0.0%

0.2%

0.4%

0.6%

0.8%

t-3 t-2 t-1 t t+1

0.2%

0.7%

-0.5% -0.4% -0.2%

-1.0%

-0.5%

0.0%

0.5%

1.0%

t-3 t-2 t-1 t t+1

 Non-election periods  Election periods ― Gap (“election effect”)

Q3

Q4 Q1

Q2

Q3

-2.0%

0.0%

2.0%

4.0%

t-3 t-2 t-1 t t+1

Nominal GDP

0.9%

0.1%

-1.1% -0.9%

-1.1%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

t-3 t-2 t-1 t t+1

Source: BPS, BI, calculations by BCA Economist

… which can have a small positive effect on growth

Average deviation

from trend: ^ Non-election periods  Election periods ― Gap (“election effect”)

Q3

Q4 Q1

Q2

Q3

-2.0%

0.0%

2.0%

4.0%

t-3 t-2 t-1 t t+1

Nominal GDP

0.9%

0.1%

-1.1% -0.9%

-1.1%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

t-3 t-2 t-1 t t+1

Source: BPS, BI, calculations by BCA Economist

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

t-3 t-2 t-1 t t+1

Real GDP

0.4%

-0.1% -0.1%

0.2% 0.2%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

t-3 t-2 t-1 t t+1

-1.0%

-0.5%

0.0%

0.5%

1.0%

t-3 t-2 t-1 t t+1

Price Level (GDP Deflator)

0.7%

0.4%

-0.6%

-0.8%

-0.9%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

t-3 t-2 t-1 t t+1

“Election effect” is mainly driven by fiscal and nonprofit spending

Pre-election boost is often propelled by gov’t spending … … while nonprofits spending peak at campaign season

-0.15 -0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Q1-11 Q1-13 Q1-15 Q1-17 Q1-19 Q1-21 Q1-23

-0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25 1.50

Q1-11 Q1-13 Q1-15 Q1-17 Q1-19 Q1-21 Q1-23

% YoY % YoY

Gov’t spending,

contribution to YoY RGDP growth

Nonprofits spending,

contribution to YoY RGDP growth

election period election period election period election period

0.96

0.61

0.25

0.20

Source: BPS, calculations by BCA Economist Source: BPS, calculations by BCA Economist

• Nonprofit orgs here include NGOs (of various religious, social, and ideological colorings) which are often affiliated with certain parties, and are involved in grassroots campaigning and “get out the vote” efforts.

• These boosts are partly offset by a slight decline in other items. But there is no clear, consistent pattern to this decline – it can come from investment, consumption, or inventories. The small sample size (four election cycles with sufficient data) does not help us in this regard.

-100 -80 -60 -40 -20 0 20 40

Consumer confidence seems to shadow approval ratings

-100 -80 -60 -40 -20 0 20 40

27.1

-0.4

― Economic approval index

(dispersal index, approve minus disapprove)

― Consumer confidence index

(percentage relative to neutral)

%

Source: BI, LSI, Indikator Politik Indonesia, calculations by BCA Economist

• We mentioned earlier that consumer confi- dence does not seem to track retail sales all that well (pg. 10). So what does it actually measure?

• One possible answer is that it measures the approval ratings of the incumbent govern- ment – at least on the economic aspect. In fact, it has tighter correlation to economic approval than the usual macro benchmarks (pg. 25).

• This may not be just a one-way relationship.

CCI can affect approval, but people’s per- ception of the government could also color their perception of the economy.

• This is a well-known phenomenon in the US, where supporters of the opposition party tend to see the economy as being in a much worse state compared to supporters of the governing party.

Correlation coefficient (2004-19) = +0.56

Correlation coefficient (2004-23) = +0.81

SBY Jokowi

Covid-19 pandemic

Voters respond to economic flux, but less clearly to GDP growth

-8 -6 -4 -2 0 2 4 6 8 10

-80 -60 -40 -20 0

20 vs. RGDP growth (YoY)

0

5

10

15

20 -80

-60 -40 -20 0

20 vs. CPI inflation (reversed axis, YoY)

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 -80

-60 -40 -20 0

20 vs. Unemployment (reversed axis, YoY)

Source: BPS, Bloomberg, LSI, Indikator Politik Indonesia, calculations by BCA Economist

• Approval ratings do respond to macro data in (mostly) the ex- pected ways – at least prior to the pandemic.

• One exception is GDP growth, which showed negative (albeit weak) correlation with approv- al before 2020.

• This may be statistical artifact, given the rather flat trajectory of GDP growth. But it may also be symptomatic of the relative disconnect between GDP and the more “mundane” concerns over jobs and inflation.

• Indeed, the latter seems to be our eternal dilemma. Our GDP grows faster during commodi- ty booms, but the same boom can also force the government to do an unpopular fuel hike.

Correlation = -0.49

Correlation = +0.72

Correlation = -0.31

Correlation = +0.26

-30 -20 -10 0 10 20 30 40 -80

-60 -40 -20 0

20 vs. IDR/USD (YoY)

Correlation = +0.47

Correlation = +0.08 Correlation = -0.49

Correlation = -0.20

2018 2019 2020 2021 2022 2023E GDP growth

(% YoY) 5.2 5.0 -2.1 3.7 5.3 5.0

GDP per capita (USD) 3927 4175 3912 4350 4784 5285

CPI inflation

(% YoY) 3.1 2.7 1.7 1.9 5.5 2.3

BI 7-day Repo Rate (%) 6.00 5.00 3.75 3.50 5.50 5.75

10Y government debt

yield (%) 7.98 7.04 5.86 6.36 6.92 6.60

USD/IDR exchange rate 14,390 13,866 14,050 14,262 15,568 15,173

Trade balance

(USD Billion) -8.5 -3.2 +21.7 +35.3 +54.5 +35.3

Current account balance

(% of GDP) -3.0 -2.7 -0.4 +0.3 +1.0 -0.7

Projections of macroeconomic indicators

26

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Source : BPS, Bloomberg, BCA Economist calculations Notes:

- BI 7-day Repo Rate, 10Y yield, and USD/IDR exchange rate all refers to end of year position

- 10Y yield and USD/IDR exchange rate projections refer to fundamental values; actual market values may vary depending on current sentiment and technical factors

27

Economic, Banking & Industry Research Team

PT Bank Central Asia Tbk

Economic, Banking & Industry Research of BCA Group 20^thGrand Indonesia, Menara BCA Jl. M.H Thamrin No. 1, Jakarta 10310, Indonesia Ph : (62-21) 2358-8000 Fax : (62-21) 2358-8343

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to: (62-21) 2358 8343 or email: arief_darmawan@bca.co.id

Victor George Petrus Matindas Senior Economist victor_matindas@bca.co.id +6221 2358 8000 Ext: 1058408

Elbert Timothy Lasiman Economist / Analyst Elbert_lasiman@bca.co.id +6221 2358 8000 Ext: 1074310

Firman Yosep Tember Research Assistant firman_tember@bca.co.id +6221 2358 8000 Ext: 20378 Agus Salim Hardjodinoto

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