---
license: other
license_name: ifpri-terms-of-use
license_link: https://www.ifpri.org/about/dataset-terms-of-use
language:
- en
tags:
- africa
- africa-rising
- ifpri
- household-survey
- agriculture
pretty_name: "Productivity-Real Exchange Rate Nexus: Revisiting the Balassa-Samuelson Hypothes"
---

# Productivity-Real Exchange Rate Nexus: Revisiting the Balassa-Samuelson Hypothesis for Emerging Asia

**Source:** [Harvard Dataverse — doi:10.7910/DVN/2RMBET](https://doi.org/10.7910/DVN/2RMBET)
**Publisher:** Harvard Dataverse
**Authors:** Ishaq, Maryam
**Files in dataset:** 72

This data set comprises of real exchange rate and productivity differential of ten emerging Asian countries against U.S. The real exchange rate series is constructed by using CPI, GDP deflator and GDP defaltor (for non-tradable sectors only). The productivity series (average productivity of labor) a

## Files

- `Chapter 5-Graphs.tab` (0.00 MB · 38 rows)
- `Chapter 5.tab` (0.00 MB · 38 rows)
- `Chapter 6-Graphs.tab` (0.00 MB · 31 rows)
- `Chapter 6.tab` (0.00 MB · 34 rows)
- `Chapter 7-Graphs.tab` (0.00 MB · 29 rows)
- `Chapter 7.tab` (0.00 MB · 29 rows)
- `Chapter 8-Graphs.tab` (0.00 MB · 29 rows)
- `Chapter 8.tab` (0.01 MB · 29 rows)
- `Chapter 9.tab` (0.01 MB · 29 rows)
- `country.tab` (0.01 MB · 387 rows)
- `er1.tab` (0.08 MB · 430 rows)
- `er2.tab` (0.03 MB · 430 rows)
- `er_adj.tab` (0.01 MB · 430 rows)
- `er.tab` (0.06 MB · 430 rows)
- `finaldata.tab` (0.10 MB · 440 rows)
- `gdpva_1.tab` (0.10 MB · 209 rows)
- `gdpva_2.tab` (0.08 MB · 484 rows)
- `gdpvacur_1.tab` (0.10 MB · 209 rows)
- `gdpvacur_2.tab` (0.08 MB · 484 rows)
- `gdpvacur_3.tab` (0.30 MB · 484 rows)
- `gdpvacur.tab` (0.10 MB · 209 rows)
- `gdpva.tab` (1.68 MB · 4,509 rows)
- `HongKong_1.tab` (0.00 MB · 31 rows)
- `HongKong_2.tab` (0.00 MB · 31 rows)
- `HongKong.tab` (0.03 MB · 307 rows)
- `ilo1970_2008_1.tab` (0.33 MB · 4,058 rows)
- `ilo1970_2008.tab` (1.59 MB · 13,577 rows)
- `ilo2009_2013.tab` (0.01 MB · 128 rows)
- `Indonesia_1.tab` (0.00 MB · 30 rows)
- `Indonesia_2.tab` (0.01 MB · 30 rows)
- `Indonesia.tab` (0.04 MB · 464 rows)
- `Japan_1.tab` (0.00 MB · 39 rows)
- `Japan_2.tab` (0.01 MB · 39 rows)
- `Korea_1.tab` (0.00 MB · 38 rows)
- `Korea_2.tab` (0.01 MB · 38 rows)
- `Korea.tab` (0.05 MB · 537 rows)
- `Malaysia_1.tab` (0.00 MB · 27 rows)
- `Malaysia_2.tab` (0.01 MB · 27 rows)
- `Malaysia.tab` (0.03 MB · 343 rows)
- `Pakistan_1.tab` (0.00 MB · 35 rows)
- `Pakistan_2.tab` (0.00 MB · 35 rows)
- `Pakistan.tab` (0.03 MB · 383 rows)
- `panel_1a.tab` (0.03 MB · 364 rows)
- `panel_1b.tab` (0.02 MB · 273 rows)
- `panel_1.tab` (0.07 MB · 364 rows)
- `panel_2.tab` (0.06 MB · 420 rows)
- `panel_3.tab` (0.13 MB · 485 rows)
- `panel_4.tab` (0.13 MB · 380 rows)
- `panel_5.tab` (0.58 MB · 440 rows)
- `panel_6.tab` (0.60 MB · 440 rows)
- `panel_7.tab` (0.33 MB · 440 rows)
- `Philippines_1.tab` (0.00 MB · 37 rows)
- `Philippines_2.tab` (0.01 MB · 37 rows)
- `Philippines.tab` (0.04 MB · 454 rows)
- `secprice_1.tab` (0.46 MB · 440 rows)
- `secprice.tab` (0.44 MB · 484 rows)
- `secprice_us.tab` (0.01 MB · 44 rows)
- `Singapore_1.tab` (0.00 MB · 32 rows)
- `Singapore_2.tab` (0.01 MB · 32 rows)
- `Singapore.tab` (0.04 MB · 488 rows)
- `Sri Lanka.tab` (0.02 MB · 219 rows)
- `SriLanka.tab` (0.02 MB · 219 rows)
- `Thailand_1.tab` (0.00 MB · 38 rows)
- `Thailand_2.tab` (0.01 MB · 38 rows)
- `Thailand.tab` (0.03 MB · 442 rows)
- `United States_1.tab` (0.00 MB · 39 rows)
- `UnitedStates_1.tab` (0.00 MB · 39 rows)
- `United States_2.tab` (0.01 MB · 39 rows)
- `UnitedStates_2.tab` (0.01 MB · 39 rows)
- `United States.tab` (0.03 MB · 421 rows)
- `UnitedStates.tab` (0.03 MB · 421 rows)
- `us_emp_3.tab` (0.00 MB · 44 rows)

The primary table loaded as `train` is **`gdpva.tab`**.

## Schema (primary file)

| Column | Type |
|--------|------|
| `country` | object |
| `cid` | int64 |
| `component` | object |
| `var3` | float64 |
| `var4` | float64 |
| `var5` | float64 |
| `var6` | float64 |
| `var7` | float64 |
| `var8` | float64 |
| `var9` | float64 |
| `var10` | float64 |
| `var11` | float64 |
| `var12` | float64 |
| `var13` | float64 |
| `var14` | float64 |
| `var15` | float64 |
| `var16` | float64 |
| `var17` | float64 |
| `var18` | float64 |
| `var19` | float64 |
| `var20` | float64 |
| `var21` | float64 |
| `var22` | float64 |
| `var23` | float64 |
| `var24` | float64 |
| `var25` | float64 |
| `var26` | float64 |
| `var27` | float64 |
| `var28` | float64 |
| `var29` | float64 |
| ... | (47 columns total) |

## Usage

```python
from datasets import load_dataset
ds = load_dataset("electricsheepasia/asia-dataverse-asia-productivity-real-exchange-rate-nexus-revisiting-the-ba")
df = ds["train"].to_pandas()
```

## Citation

```
@misc{africa_rising_doi_10_7910_dvn_2rmbet,
  title     = {Productivity-Real Exchange Rate Nexus: Revisiting the Balassa-Samuelson Hypothesis for Emerging Asia},
  author    = {Ishaq, Maryam},
  year      = {2024},
  publisher = {Harvard Dataverse},
  doi       = {10.7910/DVN/2RMBET},
  url       = {https://doi.org/10.7910/DVN/2RMBET}
}
```

## License

This dataset is released under the [Harvard Dataverse Datasets Terms of Use](https://www.ifpri.org/about/dataset-terms-of-use).
Repackaged in ML-ready Parquet format by [Electric Sheep Asia](https://huggingface.co/electricsheepasia).