Adjustments along many margins

We have spent time in class reviewing how firms can adjust to prices by changing no only quantities, but other margins as well.  Here's an example from the Next case 

Para 396: "in the early 2000s paid rest breaks which sales consultants had received were removed following the introduction of the national minimum wage".

How much would European productivity growth rise if our hi-tech sector were more like the US?

 

   The Draghi report assigns slow EU productivity growth to a large range of factors.  He mentions in particular the tech sector

““…the productivity gap between the EU and the US is largely explained by the tech sector. (p.2)

“The EU economy has traditionally been strong in all mid-technology sectors” (p.20)

 

2.      So what do the data say?  We have used EUKLEMS/INTANProd as follows.

3.      Split the economy up into

a.      ICT equipment manufacturing: C26.  Call this ICT manufacturing

b.     Information services.  Sector J: writing software, making movies etc.  call this ICT services

c.      Everything else. Call this ICT using

4.      Write productivity growth as a share-weighted average of productivity growth in all the sectors

 

 

Where the shares are shares in value-added and the same equation applies for TFP growth.

 

5.      Average annual growth rates, 1997-2019 are below for the US, EU9 (9 major EU countries) and the UK

 

US	share in GVA	LPG	TFPG
ICTusing	87%	1.91	0.44
ICTmfr	3%	12.90	10.40
ICTsvc	10%	4.88	1.86
Total		2.51	0.85
EU 9
ICTusing	91%	1.02	0.15
ICTmfr	2%	6.43	5.14
ICTsvc	7%	3.08	1.86
Total		1.25	0.35
Total with :
US shares		1.57	0.46
with  US prod		2.29	0.69
UK
ICTusing	89%	1.32	0.20
ICTmfr	1%	12.00	11.30
ICTsvc	10%	7.67	6.72
Total		2.08	0.98
Total with :
US shares		1.64	0.52
with  US prod		2.35	0.71

 

 

Where the colums are

a.      The share of that sector in the total economy

b.     Average labour productivity growth (LPG)

c.      Average TFP growth (TFPG)

And the row marked total is the weighted average.

 

The table tells us:

a.      The US has a higher GVA share of ICT manufacturing and ICT services. 

b.     But it also has higher productivity in those sectors than the EU (but not the UK).

c.      Thus the italics show two counterfacturals

a.      EU and UK productivity growth with the US shares (but EU and UK productivity growth)

b.     EU and UK productivity growth with the US productivity growth (but EU and UK productivity shares)

 

What do we find?

a.      Most of the EU/US gap is not because of industrial structure.  If the EU had the same industrial structure as the US, it would only close about 25% of the productivity gap.  The problem is that the EU has lower productivity within those sectors (and low productivity in the ICT-using sector)

b.     The UK by contrast is closer in industry structure to the US  and has high productivity in these sectors. The UK problem is low productivity in the ICT using sector.

Natural experiments and internal/external validity

Scanning an old piece by the ever-brilliant Ed Leamer.  He says "Our understanding of causal effects in macroeconomics is virtually nil, and will remain so."

I have a lot of sympathy with this after my time on the MPC.  It's worth remembering that the model is as he sets out

where 

1. x is the treatment 

2. y is the response

3. z are interactive confounders

4. w are additional confounders.

The treatment effect in macro we would like to estimate is . 

As he says

"The big problem with randomized experiments is not additive confounders; he big problem with randomized experiments is not additive confounders; it’s the interactive confounders. This is the heterogeneity issue that especially t’s the interactive confounders. This is the heterogeneity issue that especially concerns Heckman (1992) and Deaton (2008) who emphasized the need to study oncerns Heckman (1992) and Deaton (2008) who emphasized the need to study “causal mechanisms,” which I am summarizing in terms of the interactive causal mechanisms,” which I am summarizing in terms of the interactive z variables" 

 

"With interactive confounders explicitly included, the overall treatment effect ith interactive confounders explicitly included, the overall treatment effect β0 + β′ zt is not a number but a variable that depends on the confounding effects. s not a number but a variable that depends on the confounding effects. Absent observation of the interactive compounding effects bsent observation of the interactive compounding effects z, what is estimated is what is estimated is some kind of average treatment effect which is called by Imbens and Angrist (1994) ome kind of average treatment effect which is called by Imbens and Angrist (1994) a “Local Average Treatment Effect,”" 

"absent observation of z, the estimated treatment effect should be transferred only into those settings in which the confounding into those settings in which the confounding interactive variables have values close to the mean values in the experiment." 

"This is the error made by the bond rating agencies in the recent fi nancial nancial crash—they transferred fi rash—they transferred fi ndings from one historical experience to a domain in ndings from one historical experience to a domain in which they no longer applied because, I will suggest, social confounders were not hich they no longer applied"