stock flow modelling and agent based modelling
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08/10/2012 Project Title Goes Here Presenta(on to: INET@Oxford/CABDYN, Said Business School,Oxford 26/02/2013
Agent based models and stock flow consistent models: a coherent
alterna@ve? Stephen Kinsella
University of Limerick
• Funded with a series of grants from the Ins@tute for New Economic Thinking, INET, Rannis, Sta@s@cs Iceland, and Irish Research Council.
• Overarching goal is to build a workable model comparable to models used in CBs/Govt Departments for policy evalua@on/counterfactual scenario tes@ng.
Today • Context. • Stock flow consistent methodology. What is it? • SFC+ABM: Why connect SFC models to agent Based Models?
• 2 Applica@ons – Irish INET model basics • Irish economic situa@on from a balance sheet perspec@ve
– SFC ABM (Kinsella et al, EEJ, 2011) • Plan of Further Work
Context: Irish Output and Unemployment: Not good
!200.0%
!100.0%
0.0%
100.0%
200.0%
300.0%
400.0%
1998%
1998%
1999%
2000%
2000%
2001%
2002%
2002%
2003%
2004%
2004%
2005%
2006%
2006%
2007%
2008%
2008%
2009%
2010%
2010%
2011%
2012%
Constant%Price%Gross%Domes<c%Product%Index%2005:Q1=100,%Quarterly,%Seasonally%Adjusted%
Unemployment%Level:%Survey!Based,%Index%2005:Q1=100,%Quarterly,%Seasonally%Adjusted%
Sans Mul@na@onals:
SFC MODELING. WHAT IS IT? Part 1/4
SFC: Horrible name, good idea. • Tobin (1982) in his Nobel Lecture and Godley and Lavoie
(2007), illustrated the generality of these concepts by se`ng out a model of the economy based on a flow-‐of-‐funds matrix.
• Each column shows a sector’s balance sheet (for stocks) or sources and uses of funds (flows).
• Meanwhile, a row shows the stock or flow of an asset as it is distributed among the supplying and demanding sectors.
• Approach now common in simula@ng models, but macro-‐econometric applica@ons are scarce because of the consistency of the data mainly from balance sheet with those of the real economy (Na@onal Accounts).
Stock flow consistent models • Morris A. Copeland (1949) is the father of the Flow of Funds
accoun@ng. (Federal Reserve Bureau Z.1 Release). • Copeland’s idea was to enlarge the social accoun@ng
perspec@ve -‐ up to that moment used mainly in the study of na@onal income -‐ to the study of money flows.
• Essen@ally trying to find an answer to fundamental economic ques@on:
‘when total purchases of our na@onal product increase, where does the money come from to finance them? When purchases of our na@onal product decline, what becomes of the money that is not spent?’ (Copeland, 1949, p. 254)
Tobin 1982, Nobel Lecture
These models should have 1. Precision regarding @me. 2. Tracking of stocks. 3. Several assets and rates of return. 4. Modeling of financial and monetary policy opera@ons. 5. Walras’s Law and adding up constraints.
J. Tobin. Money and finance in the macroeconomic process. Journal of Money, Credit and Banking, 14(2):171–204, 1982.
Joan Robinson
“Before a model can be confronted with empirical tests, it has to be examined for internal consistency and for the a priori plausibility of its assump@ons”
-‐-‐-‐Joan Robinson, What are the quesFons? JEL 14(4) 1977, pp. 1319-‐1320.
Godley & Lavoie • Sectoral models • Set up balance and transac@on matrices • Build a model’s equa@ons from the balance sheet rela@ons (Behavioural and Iden@ty rela@ons)
• Solve for steady state • Shock using ‘policy experiments’ through simula@on.
• Lem open the ques@on of es@ma@ng these models.
• This is my group’s central problem.
Evolu@on of stock flow models: sectors
Godin et al, 2013 Stock flow consistent modeling through the ages, Levy Ins@tute WP 745
Evolu@on of Stock Flow Models: Assets
-240,000
-200,000
-160,000
-120,000
-80,000
02 03 04 05 06 07 08 09 10
Non-Financial Corporations
Net Financial Wealth (Assets - Liabilities)
-80,000
-40,000
0
40,000
80,000
02 03 04 05 06 07 08 09 10
Financial Corporations
-80,000
-60,000
-40,000
-20,000
0
20,000
02 03 04 05 06 07 08 09 10
General Gov ernment
40,000
60,000
80,000
100,000
120,000
140,000
02 03 04 05 06 07 08 09 10
Households
-300,000
-200,000
-100,000
0
100,000
02 03 04 05 06 07 08 09 10
Total Economy
-15,000
-10,000
-5,000
0
5,000
10,000
15,000
02 03 04 05 06 07 08 09 10
Non-Financial Corporations
Net financial Borrow ing/Lending
-60,000
-40,000
-20,000
0
20,000
02 03 04 05 06 07 08 09 10
Financial Corporations
-16,000
-12,000
-8,000
-4,000
0
4,000
02 03 04 05 06 07 08 09 10
General Gov ernment
-10,000
-5,000
0
5,000
10,000
15,000
02 03 04 05 06 07 08 09 10
Households
-10,000
-5,000
0
5,000
10,000
02 03 04 05 06 07 08 09 10
Total Economy
• Constantly balancing completeness off against complexity
• Want this to be as policy-‐relevant as possible
• Es@ma@ng SFC models is very hard, especially porpolio balance equa@ons.
• Consistency/Frequency/Bubble issues/Transfer pricing
Data Es@ma@on
Equa@ons Applica@on
Issues/Problems to solve
Real world balance sheet.
2011Q1Balance sheet A L A L A L A L A LG & SDRs 841 841Deposits 34,461 358,423 17,907 122,776 183,280 1Bonds 233 451,093 69,945 455 381,371 -1Loans 84,852 602,826 46,207 184,912 286,855 0Equities 150,940 557,115 17,539 46,261 644,255 0ITR 3,511 208,755 125,895 79,349 0Other 10,489 1,045 2,304 5,553 14,783 0Wealth (A-L) -208,542 -70,578 -78,402 104,922 253,441 -841Sum (A-L) 00 0 0 0 0
NFC FC G HH ROW
Simplified
2011Q1Balance sheet A L A L A L A L A LDeposits 34,461 358,423 17,907 122,776 183,280 1Bonds 233 451,093 69,945 455 381,371 -1Loans 84,852 602,826 46,207 184,912 286,855 0Equities 150,940 557,115 17,539 46,261 644,255 0Wealth (A-L) -201,564 138,381 -80,706 -15,420 159,309 0Sum (A-L) 00 0 0 0 0
NFC FC G HH ROW
FINANCIAL'BALANCE'SHEET
IRISH'ECONOMY' ROW' ''
sum'INSTITUTIONAL'SECTOR'
NFCs' FCs' ' GG' ' HHs' 'A' L' A' L' A' L' A' L' A' L' '
Physical'capital' !!' ' ' ' ' ' ' ' ' ' !!''
FINANCIAL'INSTRUMENT'
Deposits' !!,!! ' ' ' !!
!' !!,!! ' ' !!,!
! ' ' !!,!! ' ' 0'
!!"!"# ' !!,!,!! ' ' !!,!,!! ' ' ' !!! ' !!,!,!! ' ' ' !!!' 0'Loans' ' !!,!! ' !!!' ' ' !!,!! ' ' !!,!! ' ' !!,!! ' 0'Equities' ' !!!' ' !!!' !!,!,!! ' ' !!,!,!! ' ' !!,!,!! ' ' 0'
Wealth'(AGL)'' ' !!' ' !!' ' !! ' ' !!' ' !!' −!!'Sum'(AGL)' 0' 0' 0' 0' 0' 0'
Theore@cal Balance Sheet
Simula@on studies
• Kinsella & Khalil 2011 Debt Defla@on Traps within Small Open Economies
• Kinsella & Khalil 2011 Bad Banks Choking Good Banks: Simula@ng Balance Sheet Contagion
• Kinsella & Godin 2012 Leverage, Liquidity and Crisis: A Simula@on Study
Es@ma@on Studies
• O’Shea & Kinsella (2010) Solu@on and Simula@on of Large Stock Flow Consistent Monetary Produc@on Models Via the Gauss Seidel Algorithm
• Godin et al (2012) Method to Simultaneously Determine Stock, Flow, and Parameter Values in Large Stock Flow Consistent Models
• Work in progress w/ Rudi Von Arim (UTAH) on ‘solving’ and studying SFC matrices numerically.
Agent based Studies
• Kinsella, Greiff & Nell Income Distribu@on in a Stock-‐Flow Consistent Model with Educa@on and Technological Change Eastern Economic Journal, Vol. 37, Issue 1, pp. 134-‐149, 2011
• New IRC & INET grants w/ Mauro Gallega@ & Joe S@glitz to bring ABM approach closer to SFC & Vice versa.
Pure Sta9c Simula9on • Calibra@on • Sta@c parameters
• No empirical data
• Coherent macro ra@o criteria, eg. Debt/GDP
Pure Dynamic Simula9on • Calibra@on • Dynamic parameters ∆ period by period
• No Empirical data
• Coherent macro ra@o criteria, e.g. Debt/GDP
Empirical simula9on • Empirical calibra@on
• Real world data • Dynamic parameters
• Natural macro ra@o coherent
• More constraints in calibra@on
• Use country balance sheets.
Es9mated SFC Model • No balance sheets, par@al es@ma@on
• No balance sheets, full es@ma@on
• Par@al Balance sheets, full es@ma@on.
• Full balance sheets, full es@ma@on.
A word on closures. Lance Taylor (1991: 41): ‘Formally, prescribing closure boils down to sta@ng which variables are endogenous or exogenous in an equa@on system largely based upon macroeconomic accoun@ng iden@@es, and figuring out how they influence one another ... . A sense of ins@tu@ons and history necessarily enters into any serious discussion of macro causality’
Adjustment Processes. The adjustment processes within the model towards the steady state will be based on simple reac@on func@ons to disequilibria.
Note that the empirical values for adjusted GDP, and GNP, are not directly comparable to standard SNA 95 defini@ons. An example will show you why.
Shock & Results
SFC + ABM. WHY? Part 3/4.
SFC
Sectoral
No black holes
Avoids lots of neoclassical modeling problems
Focus on closures
Needs solu@on methods
ABM
Much more developed, connec@ons to complexity/network theory/etc
Individual rather than sectoral
Porpolio es@ma@on/simula@on v. easy
Models agent interac@ons more naturally
Focus on empirical regulari@es eg power laws
A PRIMITIVE SFC/ABM. Part 4/4
SFC model with interac@ng agents • 4 Sectors, households, firms, banks, government. • Workers...
– search for work. – work for a wage or get dole. – spend money on consump@on. – spend money on educa@on.
• Firms... – hire workers. – pay wages. – receive revenue from selling output.
• Government: collects taxes and provides dole. • Banks lend out, can go broke. • Model allows for changes in educa@on/employment/income/
wealth
Nice features
• no representa@ve agent • no u@lity func@on • no ra@onal expecta@ons • large number of heterogeneous agents • individual behavior is unpredictable • individuals follow simple rules • indeterminacy at the micro level (random selec@on from a given distribu@on)
• SFC Adding up constraints.
Movie.
Cool stuff: Measuring Mobility
• Via G.S. Fields & E.A. Ok, “Measuring Movement of Income”, Economica (1999).
• Mb=1/N*∑ |log m_{0}−log m_{1}|
• Implies Higher savings → lower mobility.
Conclusion & Further Work
• Promising connec@ons/crossovers • Benchmark model to be built, an INET group exists for this now.
• Lots of unexplored areas, open ques@ons, low hanging and high-‐hanging fruit.
• Fun @mes ahead!
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