Data for 2016
Total Factor Productivity Level, 2016
2016, as GGDC’s 2025 release gives it · stored as published, never rewritten
Total factor productivity measures how much output an economy gets from its capital, its workers and their schooling, compared with the United States in the same year. A level of 0.5 means the country produces about half what the US would with the same inputs. It is the Penn World Table's best-known measure, and the standard way economists compare how efficiently countries use what they have.
Total Factor Productivity Level, 2016 covers 120 countries. Macau is highest, at 1.30332; Burundi is lowest, at 0.21566. The middle country reads 0.65079. Against 2015, 119 values changed (79 up, 40 down), the same countries are covered.
Total Factor Productivity Level · Data for 2016
HighestMacau
1.30332LowestBurundi
0.21566Shaded by value in five groups of equal size, darkest at the better end.
01Values only
The table
Every country and every column of Total Factor Productivity Level, 2016, as published. The file carries values only, so no position is shown. “=” marks a shared position.
Showing 25 of 120 countries · select a heading to sort
MACEastern Asia | 1.30332 |
MUSEastern Africa | 1.20891 |
EGYNorthern Africa | 1.19512 |
SDNNorthern Africa | 1.11575 |
IRLNorthern Europe | 1.08626 |
DEUWestern Europe | 1.01068 |
NORNorthern Europe | 1.00763 |
USANorthern America | 1.00000 |
LUXWestern Europe | 0.97990 |
FRAWestern Europe | 0.96907 |
CHEWestern Europe | 0.96304 |
NLDWestern Europe | 0.95115 |
TURWestern Asia | 0.92947 |
BELWestern Europe | 0.92614 |
DNKNorthern Europe | 0.92367 |
SWENorthern Europe | 0.92130 |
POLEastern Europe | 0.90335 |
IRNSouthern Asia | 0.90082 |
PANCentral America | 0.89591 |
NZLAustralia and New Zealand | 0.87815 |
AUTWestern Europe | 0.86782 |
ISLNorthern Europe | 0.86091 |
GBRNorthern Europe | 0.84781 |
AUSAustralia and New Zealand | 0.84697 |
ESPSouthern Europe | 0.84624 |
TWNEastern Asia | 0.84546 |
FINNorthern Europe | 0.84352 |
CANNorthern America | 0.83757 |
SGPSouth-eastern Asia | 0.83429 |
CHLSouth America | 0.82908 |
ARGSouth America | 0.82316 |
URYSouth America | 0.81492 |
MLTSouthern Europe | 0.79821 |
SWZSouthern Africa | 0.79777 |
CRICentral America | 0.79376 |
BGREastern Europe | 0.78346 |
FJIMelanesia | 0.77832 |
TTOCaribbean | 0.77218 |
ROUEastern Europe | 0.76122 |
ITASouthern Europe | 0.76062 |
LTUNorthern Europe | 0.74738 |
ISRWestern Asia | 0.74736 |
CYPWestern Asia | 0.74628 |
CIVWestern Africa | 0.72177 |
HKGEastern Asia | 0.71790 |
MEXCentral America | 0.70432 |
ARMWestern Asia | 0.70407 |
BHRWestern Asia | 0.69964 |
LKASouthern Asia | 0.69951 |
SAUWestern Asia | 0.69269 |
TUNNorthern Africa | 0.68800 |
PRTSouthern Europe | 0.68726 |
JPNEastern Asia | 0.68639 |
HRVSouthern Europe | 0.67865 |
ESTNorthern Europe | 0.67750 |
KAZCentral Asia | 0.66991 |
PRYSouth America | 0.66904 |
KOREastern Asia | 0.66859 |
KWTWestern Asia | 0.66119 |
ZAFSouthern Africa | 0.65357 |
GTMCentral America | 0.64801 |
NAMSouthern Africa | 0.64632 |
SVKEastern Europe | 0.64146 |
BWASouthern Africa | 0.63538 |
DOMCaribbean | 0.63504 |
MDAEastern Europe | 0.63033 |
SVNSouthern Europe | 0.62806 |
IRQWestern Asia | 0.61552 |
MYSSouth-eastern Asia | 0.60794 |
HUNEastern Europe | 0.60354 |
CZEEastern Europe | 0.60209 |
COLSouth America | 0.59616 |
LVANorthern Europe | 0.58322 |
ALBSouthern Europe | 0.56601 |
JORWestern Asia | 0.56578 |
NGAWestern Africa | 0.56014 |
GRCSouthern Europe | 0.54923 |
PHLSouth-eastern Asia | 0.53763 |
SRBSouthern Europe | 0.53658 |
MRTWestern Africa | 0.52354 |
THASouth-eastern Asia | 0.52060 |
QATWestern Asia | 0.51273 |
MARNorthern Africa | 0.50761 |
BENWestern Africa | 0.50546 |
SLEWestern Africa | 0.50519 |
RUSEastern Europe | 0.50514 |
BRASouth America | 0.50145 |
SLVCentral America | 0.49577 |
KGZCentral Asia | 0.48925 |
GABMiddle Africa | 0.48279 |
LAOSouth-eastern Asia | 0.48182 |
SENWestern Africa | 0.47536 |
PERSouth America | 0.47323 |
ZWEEastern Africa | 0.46582 |
ECUSouth America | 0.45687 |
BOLSouth America | 0.44344 |
NICCentral America | 0.44162 |
KENEastern Africa | 0.43598 |
IDNSouth-eastern Asia | 0.43591 |
BFAWestern Africa | 0.43164 |
CHNEastern Asia | 0.42026 |
CMRMiddle Africa | 0.42019 |
BRBCaribbean | 0.40423 |
INDSouthern Asia | 0.40230 |
HNDCentral America | 0.40027 |
MNGEastern Asia | 0.38593 |
JAMCaribbean | 0.38442 |
LSOSouthern Africa | 0.36992 |
TZAEastern Africa | 0.36227 |
AGOMiddle Africa | 0.36075 |
UKREastern Europe | 0.35734 |
RWAEastern Africa | 0.35123 |
TGOWestern Africa | 0.31452 |
MOZEastern Africa | 0.28987 |
ZMBEastern Africa | 0.28971 |
VENSouth America | 0.27078 |
NERWestern Africa | 0.25579 |
CAFMiddle Africa | 0.22550 |
TJKCentral Asia | 0.22058 |
BDIEastern Africa | 0.21566 |
02In 2016
At either end
The 5 countries at each end of the headline.
Lowest
Burundi0.21566
Tajikistan0.22058
Central African Republic0.22550
Niger0.25579
Venezuela0.27078
A higher value is the better result. The middle country reads 0.65079. “Shared” marks a value another country also holds.
032015 → 2016
Since 2015
- +0 / −0countries joined / left
- 119values changed, of 120 in both
- 79 · 40rose · fell
- 1unchanged
Rose most
Fell most
Trinidad and Tobago0.89634 → 0.77218−0.12416
Ireland1.19812 → 1.08626−0.11186
Macau1.41301 → 1.30332−0.10968
Venezuela0.36934 → 0.27078−0.09856
Qatar0.59798 → 0.51273−0.08525
04Caveats
Read before you use
One year of the 2025 release
Every year in this series comes from GGDC’s 2025 release, recalculated on one method, so a change from one year to the next is not a revision. It can differ from what was first published for 2016.
Nothing missing
Every one of the 120 countries has every column.
05The files
Download and cite
- .csv
For a spreadsheet or code
120 rows · 4.9 KB · UTF-8, opens in Excel
Opens with 11 lines of source notes; the table starts on row 13.
Download total-factor-productivity-2016-nations-inquiry.csv - ↗
The publisher’s original
GGDC’s own file, on its own site.
554105
What this site changed: Reshaped to one row per country, with its ISO code; no value recalculated, rescaled or rounded. In full
Licence: CC BY 4.0 · what it allows, in plain words
Cite this edition
Groningen Growth and Development Centre (GGDC) (2016). Total Factor Productivity Level, 2016 [data set], describing 2016. As held by Nations Inquiry, https://nationsinquiry.com/datasets/total-factor-productivity/2016
0654 held
Other years
‹ The year before
Total Factor Productivity Level, 2015120 countries
The year after ›
Total Factor Productivity Level, 2017120 countries
All of them
Total Factor Productivity Level: every year54 held, with the data dictionary, coverage and licence.
How it has moved, charted by country