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Unconventional monetary policy and commercial real estate sector: A financial social accounting

matrix for Italy

Irfan Ahmed, Preston University Islamabad, Pakistan Claudio Socci, University of Macerata, Italy

Rosita Pretaroli, University of Macerata, Italy Francesca Severini, University of Macerata, Italy

Qaiser Rafique Yasser, Preston University Islamabad, Pakistan

Recent trends in the real estate market and its analysis 2017 edition 21 – 23 November 2017, Warsaw, Poland

• The recent global financial crises stoke the debate on economic or financial origins of downturns and expansions of economies.

• Open questions: - Whether financial crises worsen significantly countries’ fiscal position? - Whether monetary policy leads to the economic downturns/expansions? - Are there interactions between financial institutions and real sectors of

the economy?

INTRODUCTION

Unconventional monetary policy and commercial real estate sector: A financial social accounting matrix for Italy

• Some researches posit that sharp declines in money supply lead to the sharp decline in output, while sharp increase in the growth of money leads to the sustained inflation (Bordo & Rockoff, 2013, Friedman & Schwartz, 1963a; 1963b).

• Thus they conclude that the Great Depression of 1929-1933 was the result of an idiosyncratic perturbance of the money stock, while the inflations during World Wars were precipitations of war time issues of fiat money.

• On the contrary, the other school of thought maintains that the monetary policy has no or very little relationship with the real economy. Believers of this thought present that it was the collapse of real economic industry that induced the liquidity driven panics and resulted to the events of 1929-1933 (Calomiris & Mason 2003; Temin 1976).

INTRODUCTION


• For Great Depression 1929-1933, they argue that there were some non-monetary factors that influenced the business cycles. One of them was a crash of stock market in 1929 that lead to the rise in income uncertainty (Romer, 1990; Romer & Romer, 2013).

• Several studies posit that financial crises worsen significantly countries’ fiscal position, both in terms of deficit and debt (Laeven & Valencia, 2008; 2012; Reinhart & Rogoff, 2009; 2011).

• There are widespread interactions between financial institutions and real sectors of the economy (Dakila, Bayangos & Ignacio, 2013)

INTRODUCTION


• Real estate sector is one of the economic sectors which present direct and indirect nexus with the financial market (Nobili & Zollino, 2017)

• In this scenario it is imperative to have a framework able to identify the origins and the policies to push towards expansion or contraction

• Financial Social Accounting Matrix and CGE model allows to test for many countries the relationship between economic and financial flows

INTRODUCTION


OBJECTIVE

Investigate how the monetary policy implemented by the European Central Bank (ECB) influences the Italian commercial real estate

activity in a dynamic framework.


OUTLINE

1. Financial Social Accounting Matrix (FSAM) for Italy 2009 • Economic flows • Financial flows

2. Financial Computable General Equilibrium (FCGE) Model

3. Policy Implication for the Italian Economy


1. Financial Social Accounting Matrix (FSAM)



Historical Background of Financial Accounts

• After the First World War, several studies were devoted to investigate the fluctuations in economic activity with reference to the financial accounts (Fabricant, 1984; Rutherford, 2003).

• During the Second World War, the System of National Accounts (SNA) evidenced a phenomenal insurgency and several studies were dedicated not only to the macroeconomic variables (i.e. inflation, GDP etc.) but also to the financial position of different institutional sectors. (Carson, 1975; Stone, 1966)




• The most significant figure was Morris A. Copeland (1895-1989), who published the fundamental text ‘A Study of Money flow in the United States’

• Richard Stone cited Copeland in the preparatory work for the System of National Accounts (SNA) of 1947.

• The major concerns of theories of Holtrop (1957) and Polak (1959) to

identify the sector of origin of forces pushing towards expansion or contraction by means of sectoral financial analysis




• The beginning of financial accounts in Italy is associated significantly to the work of Paolo Baffi (1911-1989) who devoted much of his work in investigating and predicting the impact of the centrals banks monetary policies on the structural changes in interest rates, costs, and productivity (Bonis and Gigliobianco, 2012).

• Wassily Leontief also devoted his work, in his later age, to the integration of financial flows in input-output models (Biscontin and Mandarino, 1983 & Leontief and Brody, 1993).



Social Accounting Matrix – SAM • The SAM integrates detailed data on production, generation,

distribution and use of income, thereby allowing a systematic description of economic transactions. (Ciaschini and Socci 2006)

• The matrix can be broken up into blocks which describe the national flows according to the whole income circular flow framework.



Commodities Industries Primary Factors Institutional

Sectors Capital Formation

Commodities INERMEDIATE CONSUMPTION

(USE TABLE) FINAL

CONSUMPTION INVESTMENTS

Industries SUPPLY TABLE

Primary Factors VALUE ADDED

Institutional Sectors PRIMARY INCOME

DISTRIBUTION

SECONDARY INCOME

DISTRIBUTION

Capital Accounts by

Institutional Sectors SAVINGS

Basic Framework of SAM



Blocks of the SAM for Economic flows

• Intermediate consumptions from the Use table

• Total output by industries from the Supply (Make) table

• Generation of Value Added

• Primary income allocation

• Secondary income allocation (current transfers among Institutional Sectors)

• Use of disposable income

• Capital formation



Financial Social Accounting Matrix - FSAM • Analyses financial interrelationships among Institutional Sectors (Hubic, 2012)

• Highlights monetary aggregates, financial investments and sources of finance

• Presents two additional accounts:

– The capital accounts – The financial assets and liabilities accounts

• The accounts of financial assets and liabilities keep the detail on the nature

and the structure of financial resources and uses of economic agents.



Commodities Industries Primary Factors Institutional

Sectors

Capital Accounts by

Institutional Sectors

Financial

Instruments

Commodities INERMEDIATE

CONSUMPTION (USE TABLE)

CONSUMPTION INVESTMENTS

Industries MAKE TABLE

Primary Factors VALUE ADDED

Institutional Sectors PRIMARY INCOME

DISTRIBION

SECONDARY INCOME

DISTRIBUTION

Capital Accounts by

Institutional Sectors SAVINGS

CAPITAL TRANSFERS

AMONG INST. SECT. LIABILITIES

Financial Instruments ASSETS

Basic Framework of FSAM


Basic framework of social accounting matrix (SAM) with real and financial accounts

Ou

tlay

s

Commodities Production

activities

Factors of Productions Taxes Trade and

transport

margins

Institutional Sectors Current Account Institutional Sectors Capital Account Ch. In Stocks Financial

instruments

Total

P1 P2 P3 P4 Firms Govt HH ROW Firms Govt HH ROW

Revenues n. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Commodities

1

Intermediate

consumption

Final

demand

by Govt

Final

demand

by HH

Exports Gross fixed capital formation /

Investment demand by institutional

sectors

Inventories

Total

demand

Production activities

2 Domestic

output

Domestic

demand for

domestic

output

Factors of

Productions

P1 3 Net value

added

Factor

income from

ROW

Net value

added P2 4

P3 5

P4 6

Taxes

7 Taxes on

commodities

Total taxes

Trade and transport

margins

8 Transaction

costs

Total trade

and

transport

margins


Current Account

Firms 9 Firms' income

Distributive transactions among institutional

sectors

Total

revenue of

institutional

sectors

Govt 10 Govt Income Taxes

HH 11 HH income

ROW 12 Imports ROW income Taxes


Capital Account

Firms

13

Firms

Savings

Capital transfers among institutional

sectors

Financial

liabilities by

institutional

sectors

Availability of

capital by

institutional

sectors Govt

14

Govt

Savings

HH

15

HH

Savings

ROW

16

ROW

Savings

Ch. in stocks

17

Inventories by institutional sectors

Total

changes in

inventories

Financial instruments

18

Financial assets by institutional sectors

Total

financial

assets

Total

19 Total supply to

the domestic

market

Domestic

output

Net value added Total taxes Total trade

and

transport

Total outlays of institutional sectors Total capital expenditures of

institutional sectors

Total changes

in inventories

Total financial

liabilities

Sources: Emini (2002), Hubic (2012) and author’s construction

Notations:P1-compensation of employees; P2-mixed income; P3-gross operating surplus; P4-other taxes less subsidies; Govt-government; HH-households; ROW-rest of the world


Data The data for SAM have been collected from the Italian statistical department (ISTAT) and from the Eurostat for the year 2009. On the other hand, the data on financial assets and financial liabilities for the year 2009 have been taken from the published accounts of Bank of Italy.



Peculiarities of the FSAM for the Italian Economy – year 2009:

64 Commodities

64 Industries

4 components of Value Added

• Compensation of Employees

• Mixed income

• Gross operating surpluses

• Taxes

4 Institutional Sectors

• Firms

• Government

• Households and ISPs

• Rest of the World

12 Financial instruments


2. Financial Computable General Equilibrium Model (FCGE)



CGE model characterization

CGE modeling attempt to determine the quantitative effects of economic

policies in the income circular flow framework (Ciaschini and Socci 2006)

• The structure of the model follows the FSAM framework

• The blocks of the FSAM inspire the blocks of the equations in the

model



Commodities Industry Primary

Factors

Institutional Sectors Capital

Accounts by

Institutional

Sectors

Financial

Instruments Private Government

Rest of

World

Commodities B(x,p) C(rd,p) G(rd,p) E(e,p) I(p)

Industry X(x,p)

Primary Factors Y(x, pf)

Inst

itu

tio

nal

Sect

ors

Private Rh(y) Trh(r,a) Trh(r,a) Trh(r,a)

Government T(x) Rg(y) Tg(r,a) Trg(r,a) Trg(r,a)

Rest of

World M(x,e) Rrow(y) Trrow(r,a) Trrow(r,a) (+/-)e

Capital Accounts by

Institutional

Sectors Sh(rd) Sg(rd) Srow(rd) CTr(s) L(s,pi)

Financial

Instruments A(s,pi)

Fundamental relationships in FCGE model




Dynamic FCGE model characterization •The structure of the model follows the FSAM framework •Financial flows •Finite Horizon maximization problem •DCGE uses growth rate g, depreciation d, interest rate r, initial investment I0, rental rate of capital RK in a base year, initial capital earning k0

•Inter-temporal capital accumulation condition •the optimization problem for all consumers in a dynamic model

•The first order conditions derived from maximization problem are:

•The corresponding mixed complimentary problem can be formulated as follows: •Market clearing conditions: •Zero profit conditions: •Income balance condition: •Equilibrium of financial instruments where; Si = savings

Ii = investment ΔAi = change in assets ΔEi = change in liabilities

The variables and parameters are: t = time periods, T = terminal period, p = individual time-preference parameter, u = utility function, Ct = consumption in period t, x = production function, Xt = total output in period t, Kt = capital in period t, Lt = labour in period t, Mt = imports in period t, Tat = indirect taxes in period t, It = investment in period t, Et = exports in period t, = capital depreciation rate, Pt = price of output in period t, d = demand function, PKt = price of capital in period t, RKt = rental of capital in period t, PLt = wage in period t, PMt = price of imports in period t, RA = consumer's disposable income.




Policy Scenario – EBondG

The European Central Bank (ECB) purchases Bonds for 10

billions of Euro (Bonds issued by Central Government)



Policy Results

The effects of the policy are measured in terms of:

Percentage change in total GDP

Percentage change in growth in commercial real estate (CRE) sector

Percentage change in value added by CRE

Percentage change in Pricing of Commercial Housing


Policy Scenario 1 (EBondG) - Impact on GDP

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

2014 2015

2016 2017

2018 2019

2020

GDP from 2014 to 2020 - % change

gdp gdp2



Policy Scenario (EBondG) - Impact on CRE growth

B…

A…

0.00%

0.30%

0.60%

0.90%

1.20%

1.50%

1.80%

2014 2015 2016 2017 2018 2019 2020

1.44%

1.48% 1.52% 1.55%

1.56% 1.55% 1.52%

1.69% 1.47% 1.52% 1.50%

1.30%

1.61% 1.51%

Benchmark After simulation

Figure 1. Change in output of CRE sector - in percent



Policy Scenario (EBondG) - Impact on value added by CRE

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

2014 2015

2016 2017

2018

2019

2020

0.84% 0.81%

0.80% 0.81%

0.82% 0.85%

0.87%

1.40%

0.83% 0.80%

0.67%

0.13%

0.91% 0.86%

Benchmark After simulation

Percentage change in value added by CRE sector



Policy Scenario (EBondG) - Impact on pricing of CRE

0.00%

-0.10%

0.00%

0.09%

0.15%

0.20% 0.23% 0.24%

-0.15%

-0.10%

-0.05%

0.00%

0.05%

0.10%

0.15%

0.20%

0.25%

0.30%

2013 2014 2015 2016 2017 2018 2019 2020

% change

Percentage change from benchmark in pricing of commercial housing


Thank you for your attention

Recent trends in the real estate market and its analysis 2017 edition 21 – 23 November 2017, Warsaw, Poland


1 Products of agriculture, hunting and related services 39 Telecommunications services

2 Products of forestry, logging and related services 40 Computer programming, consultancy and related services; information services

3 Fish and other fishing products; aquaculture products; support services to fishing 41 Financial services, except insurance and pension funding

4 Mining and quarrying 42 Insurance, reinsurance and pension funding services, except compulsory social security

5 Food products, beverages and tobacco products 43 Services auxiliary to financial services and insurance services

6 Textiles, wearing apparel and leather products 44 Real estate (excluding imputed rent)

7 Wood and of products of wood and cork 45 Imputed rents of owner-occupied dwellings

8 Paper and paper products 46 Legal and accounting services; services of head offices; management consulting services

9 Printing and recording services 47 Architectural and engineering services; technical testing and analysis services

10 Coke and refined petroleum products 48 Scientific research and development services

11 Chemicals and chemical products 49 Advertising and market research services

12 Basic pharmaceutical products and pharmaceutical preparations 50 Other professional, scientific and technical services; veterinary services

13 Rubber and plastics products 51 Rental and leasing services

14 Other non-metallic mineral products 52 Employment services

15 Basic metals 53 Travel agency, tour operator and other reservation services and related services

16 Fabricated metal products, except machinery and equipment 54 Security and investigation services; services to buildings and landscape;

17 Computer, electronic and optical products 55 Public administration and defence services; compulsory social security services

18 Electrical equipment 56 Education services

19 Machinery and equipment n.e.c. 57 Human health services

20 Motor vehicles, trailers and semi-trailers 58 Social work services

21 Other transport equipment 59 Creative, arts and entertainment services; library, archive, museum and other cultural services

22 Furniture; other manufactured goods 60 Sporting services and amusement and recreation services

23 Repair and installation services of machinery and equipment 61 Services furnished by membership organisations

24 Electricity, gas, steam and air-conditioning 62 Repair services of computers and personal and household goods

25 Natural water; water treatment and supply services 63 Other personal services

26 Sewerage; waste collection, treatment and disposal activities; materials recovery;

remediation activities and other waste management services 64 Services of households as employers

27 Constructions and construction works VA1 Compensation of Employees

28 Wholesale and retail trade and repair services of motor vehicles and motorcycles VA2 Mixed income

29 Wholesale trade services, except of motor vehicles and motorcycles VA3 Gross operating surplues

30 Retail trade services, except of motor vehicles and motorcycles VA4 Other taxes less subsidies on domestic production

31 Land transport services and transport services via pipelines FIRM Current Account of Firms

32 Water transport services GOV Current Account of Govt

33 Air transport services HH Current Account of Households and ISPs

34 Warehousing and support services for transportation ROW Current Account of Rest of the World

35 Postal and courier services CAPF Capital Account of Firms

36 Accommodation and food services CAPG Capital Account of Govt

37 Publishing services CAPHH Capital Account of Households and ISPs

38 Motion picture, video and television programme production CAPROW Capital Account of Rest of the World

Financial SAM accounts

1 Monetary gold and SDRs

2 Currency and transferable deposits

3 Other deposits

4 Short-term securities

5 Bonds

6 Derivatives

7 short-term loans

8 Medium and long-term loans

9 Shares and other equity

10 Mutual fund shares

11 Insurance technical reserves

12 Other accounts receivable/payable

Financial Instruments

Ou

tlay

s

Commodities Production

industries

Factors of Productions Taxes Institutional Sectors Current Account Institutional Sectors Capital Account Ch. In

Stock

Financial

Inst.

Total

rows

Revenues

VA1 VA2 VA3 VA4 FIRM GOV H.H ROW CAPF CAPG CAPHH

CAPR

OW

n. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Commodities 1 0 1551044 0 0 0 0 0 0 324684 929482 333714 149070 38404 107206 0 -8196 0 3425408

Production

industries

2 2919618 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2919618

Factors of

Productions VA1 3 0 650489 0 0 0 0 0 0 0 0 3316 0 0 0 0 0 0 653805

VA2 4 0 217583 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 217583

VA3 5 0 464905 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 464905

VA4 6 0 35597 0 0 0 0 0 0 0 0 6019 0 0 0 0 0 0 41616

Taxes 7 151121 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 151121


Current Account FIRM 8 0 0 0 0 318806 0 0 94680 27115 58605 46211 0 0 0 0 0 0 545417

GOV 9 0 0 0 0 28735 41616 148044 51397 694 407553 4607 0 0 0 0 0 0 682646

H.H 10 0 0 651354 217583 117364 0 0 225254 317395 188364 31542 0 0 0 0 0 0 1748856

ROW 11 354669 0 2451 0 0 0 3077 39323 43705 12360 0 0 0 0 0 0 0 455585


Capital Account CAPF 12 0 0 0 0 0 0 0 134763 0 0 0 0 24366 1 324 0 165535 324989

CAPG 13 0 0 0 0 0 0 0 0 -30947 0 0 8181 0 6143 1310 0 88276 72963

CAPHH 14 0 0 0 0 0 0 0 0 0 152492 0 0 2953 895 1 0 20805 177146

CAPRO

W 15 0 0 0 0 0 0 0 0 0 0 30176 -62248 -4204 414 0 0 61002 25140

Ch. In stock 16 0 0 0 0 0 0 0 0 0 0 0 -8230 -66 100 0 0 0 -8196

Financial Inst. 17 0 0 0 0 0 0 0 0 0 0 0 238216 11510 62387 23505 0 0 335618

Total column 18 3425408 2919618 653805 217583 464905 41616 151121 545417 682646 1748856 455585 324989 72963 177146 25140 -8196 335618

Aggregated SAM with Real and Financial Accounts

•zero profit condition

•market clearance condition for commodity

•market clearance condition for primary factors

•income balance condition

Conditions of CGE Model

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