This article was downloaded by: [University of Sussex Library] On: 03 February 2015, At: 16:06 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Biodemography and Social Biology Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/hsbi20

Seasonality of births in human populations a

David A. Lam & Jeffrey A. Miron

b

a

Department of Economics , University of Michigan , Ann Arbor, Michigan b

Department of Economics , Boston University , Boston, Massachusetts Published online: 23 Aug 2010.

To cite this article: David A. Lam & Jeffrey A. Miron (1991) Seasonality of births in human populations, Biodemography and Social Biology, 38:1-2, 51-78, DOI: 10.1080/19485565.1991.9988772 To link to this article: http://dx.doi.org/10.1080/19485565.1991.9988772

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution,

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Seasonality of Births in Human Populations

David A. Lam and Jeffrey A. Miron

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Department of Economics, University of Michigan, Ann Arbor, Michigan; and Department of Economics, Boston University, Boston, Massachusetts ABSTRACT: Seasonal fluctuations in births have been observed in virtually all human populations. In this paper we re-examine the seasonality of births with two main objectives in mind. The first is to provide an overview of the basic facts about the seasonality of births, presenting new estimates of the seasonal patterns. Seasonality is an important if not dominant source of nontrend variation in births in virtually all populations, but there are dramatic and puzzling differences across countries and time periods in the pattern of seasonal variation observed in particular populations. The second purpose of the paper is to survey the leading hypotheses about birth seasonality that have appeared in the literature and to discuss the consistency of these hypotheses with observed seasonal patterns. Using our estimates of seasonal patterns along with other evidence in the literature, we conclude that no single explanation receives strong, consistent support from the data.

Seasonal fluctuations in births have been observed in virtually all human populations, both contemporary and historical. These fluctuations have attracted considerable attention from demographers and other social scientists, and a variety of behavioral and biological mechanisms have been proposed to explain them (see, e.g., Cowgill, 1965, 1966; Rosenberg, 1966; Parkes, 1968, 1976; Kevan, 1979; Dyson and Crook, 1981; and Roenneberg and Aschoff, 1989a). Despite a long history of research on the subject, however, there is no generally accepted explanation for the seasonality of births. In this paper we re-examine the seasonality of births in human populations, with two main objectives in mind. The first is to provide an overview of the basic facts about the seasonality of births, presenting new estimates of the seasonal patterns. Existing literature provides estimates of birth seasonality for many countries and time periods, but differing

51

methodologies and the frequent use of small sample periods makes comparisons across populations difficult. We present new estimates of the seasonal patterns in births in order to document the major regularities and unify existing estimates. We do not, however, provide an exhaustive set of results (Lam and Miron, 1987). Instead, we illustrate the basic stylized facts about the seasonality of births. The empirical section of the paper produces two broad conclusions. First, seasonality is an important if not dominant source of nontrend variation in births in virtually all populations. Second, even though there is pronounced seasonal variation in almost all populations, there are dramatic and puzzling differences across countries and time periods in the pattern of seasonal variations observed in particular populations. While it is true that certain patterns appear in many countries and persist over periods as long as centuries,

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

52

Social Biology

Lam and Mirón

there is no simple rule determining 12 which seasonal pattern in births a particS, = exp ( 2 Mí j (2) ular population exhibits. The second purpose of the paper is to survey the leading hypotheses about 2 3 4 birth seasonality that have appeared in Tt = exp (yt + Si + Qt + tyt ) (3) the literature and to discuss the consis- where B, is the number of births per day tency of these hypotheses with observed in month t, St is the seasonal component seasonal patterns. Using our estimates of B,, T, is the trend component of B,, X, of seasonal patterns along with other ev- is the nonseasonal, nontrend compoidence in the literature, we conclude nent of B¡, d\ is a seasonal dummy for that no single explanation receives month s, and a s is the seasonal factor in strong, consistent support from the B, for months. data. Instead, the variation in seasonal Equations (l)-(3) imply patterns across countries and time periods poses a challenge to virtually all ex12 S isting explanations, without decisively In B, = t + V + Si2 + 6i3 rejecting any of them. The seasonality s = 1 + i4 + In Xt. (4) of births remains a major unresolved puzzle in empirical demography, a puzzle that raises provocative questions for It follows from (4) that if as is the coefboth biological and behavioral research ficient on the sth seasonal dummy, then Bt is on average as per cent higher in seaon fertility. son s than it is on average during the year as a whole. MATERIALS AND METHODS To obtain estimates of the as, we proceed in two steps. We first estimate the ESTIMATING AND COMPARING equation SEASONAL PATTERNS In order to quantify the relative importance of seasonal fluctuations and to consistently compare seasonal patterns across populations, we use a methodology based on the seasonal dummy definition of seasonality. This is a simple and easily interpreted definition, and our results can be readily compared with the estimates provided in much previous research. Alternative specifications of seasonality, such as seasonal ARIMA or spectral models, do not produce estimates of the timing and magnitude of the seasonal peaks and troughs in births. These patterns are the principal focus of our study. We assume that the data on births are described by the following model: B, = S,T,X, (1)

In B, = a + 7f + 8i2 + 0i3 + 4>t4 + bt (5) by Ordinary Least Squares (OLS). The residual from this equation, bt, is a zero mean, detrended series for the log of births. We then estimate the equation 12

b, =

+

(6)

s = 1

OLS estimates of the as are consistent; we use these as our estimates of the seasonal pattern in births. In addition to presenting estimates of the seasonal patterns, we summarize these patterns in a number of ways. We present the R2 from the OLS estimation of (6) as an estimate of the percentage of the nontrend variation in births due to seasonality, and we report the ampli-

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonality of Births

53

tude (maximum minus minimum) of the twelve seasonal coefficients as a measure of the importance of the seasonal fluctuations. Finally, we test the statistical significance of the seasonal patterns that we estimate. Since the error term in (6) is not necessarily serially uncorrelated, we employ the Newey and West (1987) formulas for the standard errors of the coefficient estimates. Our specification allows for a lag length of 12 months in the autocorrelation matrix, and it insures positive definiteness of the variance-covariance matrix by using the damp factor suggested in Newey and West (1987).

twenty years long, and all are over ten years long. There are many potential sources of bias in monthly data on births, so it is possible that the data reflect something other than true seasonal fluctuations in births. Takahashi (1964), for example, notes a serious reporting bias for Japan, and Anderson and Silver (1988) provide a detailed analysis of the effects of the Soviet birth registration system on seasonality in Soviet birth series. We believe the data used here are of high quality, but the potential for systematic reporting biases must always be kept in mind in analysis of monthly vital statistics data.

RESULTS

Is BIRTH SEASONALITY QUANTITATIVELY IMPORTANT?

THE STYLIZED FACTS ABOUT THE SEASONALITY OF BIRTHS

In this section we document the quantitative importance of seasonal fluctuations and present new estimates of the seasonal patterns in births for a sample of countries and time periods. Our goal is to illustrate the key stylized facts about birth seasonality rather than to provide an exhaustive set of estimates. A more extensive set of empirical results can be found in Lam and Miron (1987), which presents the seasonal patterns in over twenty-five countries , in many cases for long sample periods. Here we present only those patterns that are necessary to make the points that we discuss in the next section. We limit the presentation to published vital statistics data, with the exception of the Wrigley-Schofield (1981) parish reconstitution series for England, included because of the exceptionally long time period it covers. We also restrict our analysis to data series long enough to establish meaningful seasonal patterns. Our typical series is at least

Seasonality in births would merit only casual attention if the seasonal fluctuations were small in magnitude or if the patterns were highly unstable over time. As will be seen below, however, seasonal fluctuations are quantitatively large when compared to other temporal variations in fertility, and the patterns themselves are strongly persistent. The most convincing evidence on both of these points can be found in graphs of the time series of monthly births. In Figures 1 and 2 we present the monthly data on births (adjusted for the number of days in the month) for two populations with relatively large seasonal fluctuations. Figure 1 shows the monthly birth series for Georgia for the period 1948-86, while Figure 2 shows the series for Sweden for the period 1921-87. Inspection of the figures demonstrates first of all that seasonal fluctuations are large in magnitude relative to longer term secular movements in fertility. For example, the typical May to September change in births in Georgia is at least as great as the difference between the average birth rate in the mid-

54

Lam and Miron

Social Biology

6.0 —

5.6 —

5.2 —

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

4.8 —

M .H —

3 .2

| '' ' |

xlO1942

19H6

1950

19SH

1958

1962

1SB6

1970

197H

1978

1982

1986

1951

19S7

1963

1969

1975

1981

1987

FIG. 1.—Births by month, Georgia, white.

xlO3 1921

1927

1933

1939

FIG. 2.—Births by month, Sweden.

19H5

Vol. 38, No. 1-2

ro

T-H

O

1

s co

1

o

T-H

1

1

o

CS

1 t-H1

CM

CM CM

T-H T-H oo r00 m vo p gg ro in 3 CM O T-H co Tf T-H o CM CM T-H ro O *-< 1 o 1 Tf VO T-H ro Tí 00 00 CM SS ON ON 00 t-H OO o S vo O N 0 0 in m r- vo voVO 0 0 ON 00 00 Tf

P

ON

CO

74

vo CM §g oo Tf S co f£ VO T f m in in r-* inT f ro

27

VO

CM

1 1

S 2S3 T-H

1

CM m

53

94

CM

O CM

!-H

7 1 17

s

S

1

t-H

T-H

CM

t-H

1

Tf CO

5o

t—«

T-H

Tf VO Tf

m

CM CM

in in

CO Tf

TÍ

7

Tf

vo vO T-H r o

oo 1

1 ro

in 00 CM-PSÉ;0,ON 0 0 T-H co 3 VO

ON O T-H r — ON

T-H

s

o o o o VO O o co o

s s voco 00 O s co inS Tin? ro 00

vá

00 S o T-HCM in T-H CM vo S T-H T-H Tf o T-H 1 11 1 1 1 1 1 1 1 1 1 1 1

CO vo 00 0O ONvO 00 T Î S

VO

CM

00 00

r-

T-H

1

ES m

t-H oo S oro ço CMin vo ro vo in in co in 1-H in ^

'M M

» r . r .

(

Lam and Mirón

i

o

i i i

Social Biology

o r o N n o i o n r i o O r i K d h O t D ^ n o o o i o n o r i 1 1 1 1 1 7 1 1 1 1 1 1 1 7 7 7 7 7 1 7 1 1 1 1 1 1 1 1 1 1 ^ 1 1 1 1

I I I NOooNOt^fOfOuiooN^Qn^rHor^^^ONOOvNtrONvooovotNNOri^oOrHTí-nnin °°. "**. t^'-J'^OOÏ^'^'OOO^CMvOOCMONi—ivOt^-OOCM H H n O t N l y . 0 0 O ' t 0>r>^DMtTl\OiH(NlNO i

i

i

i i

i 7 i

i

i

i

i

i

i

i

i 7 7 7 7

i

i

i

i

i

i

i

i

i

i

i

i

i

i i

^^•OO^n^OH^OûOiOCi^^^HlO^iO^ûtNvOOOh-lOHNOvNiOOOOHHr'ihOOO inininoor^-'-ic^'tcncMOT-Hcoi-tocMocMOOOi-íTroooO'-i'tioooOT-tocMoocMO

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

!

I

l

i

l

i

t

i

l

t

i

l

II

^"^c^r^t^ööoöcMNOw^cMt^cnincninvdcncvitnö^^ I I I I I I I I I I I I I I I I I I I I I I I I I I ^r^ppc^vow^cMt^^^cor^^^^r^incMONNOco^vqin^t Tfcn^VOVOCMHTfCMÖ^CMcnOCMÖÖÖ^^ÖoNvOt^ON^CMÖwS^^ I I I I I I I t i l l I I I

I

t i l l

I

CM I™H f~^ co f*** oo ^f OO CO vo c^i ^ j Osj r^i ^ * s o s o ON CM t""** r^ ON r^^ *"^ i*"i *"^ »*" O t ^ - C M ' — t C M v O v O v p o o r ^ - r j - i o i

voo^í'OONOCMvooovDror-(OvoincNCMor^-'^"i--n es Tt en 00 O m m r^ O es o 1 I oo 1 1 1 1 | i T-l 1 1 1 1 11 1 1 1 11 1 1 1 0 0 Tt en es en t-00 NO c— T? §8 g Tf 00 S i-H T-H 283 i n es en in ON en t-» en en NO S S oo i n en Tt m Tt 00 CN i n m 00 00 es es esen m o o es i — i CN CN es l - H en oes csl-H Tf in cs Tt 1 1 1 1 1 1 1

00 N»

Pi

ON 00

00

97

s s

T-l

Tt

.21

.62 .74

i

o es i — I m ! 1 1

SiC

l-H

00

es en 1

ig

Tt O | 1

l-H

NO

»n PJ en

1

m

O es o

1

en 00 00 Tt NO

ON

i—l

-20

-17 56 -27 03

00 NO 00

T

S

m oo

CS l-H

m en o en 1 11

i—'

1 oo m en

»n

T1

en

en

in

es

NO

in 1

go

i-H ON i-H

-12

29

sa

en CS in0 0 TH es es

s «a 3

-17 -24

°T T vn in i-i ON es mNO en cs o

1

20

-30

47

en es

1—1 cs cs ON in en& en es in cs 1

NO O NO O N

en

1-4 CO

Tt

1-H en 11 1 i — » in oo in m Tt S in en en NO 1—* 1 1 1 1

NO NO

47

43

i-H

in es ON i-H O N

Y

1 1

8 o! S P3O l-H

S

r- in ON m

-28

-24

r^ oo m NO « t ,-H NO i-H o NO 0 0 in 1

-17

41 -37

98

47

in en ON es NO NO i n es 1

1

Oi-H

S 8 CS in en00 ss

o oo

'

m

S in S

SS

85 m ••H

Tf

l—l i-H

1 1

o o

*"~i i n NO en

1 1

NO

o O en 1 00 NO

94

Pi S CS O CN

•

m

t-

"p

74

45

en en

00 00 Tt Tt

o

.47 .29 .46 .71 .67 -2 .15 41

S S 8m g en oo ines en oo en es

1 l

T'

-10

NO ON

g

r» es

en NO O eN

T ON

NO t -

1

S

o o es 1 1 1 Tf oo en pi mi - l NO es F21—1 en oo m NO CS o cs 1 1 1 1 en

-13

1-H

I-H

1 es NO O o in NO ON e n r- ^ Tt en en r^ en ooi — i oo es o en en es Tto P!O Tt en "7e 1

o

in

-21

r - Tt

•*

es en ON en oo o r1 1

42 47

SÍS NO

'T

m 00 '~t

1

ON I — I O N

ON T t

en 1

ON en i—* ON OO 0 0 CS 00 CS

T f ON 2 CS T f CN oo r-. S 0 0

1

es

00 OO

-12

oo

00 00

in

T

ON S3 S $ S OO OO o es o T f in en en es "* T1

• — i NO T Í

o 1 1

0 0 NO

en o en en ON 1

T?

.55

Pi

20

NO

00 CS

S

1 1

34

i-H 1 — t

in NO oo tn ON esg

o

NO O

NO

15

en

Tt T- i n

1

Sj S ig s en 00

01

m

Tt

i-i

a

en O en

74

88 3 PS

in O

es

es NO NO i — i

es in i—i

ON

NO O

10

ON

T

o

S es O O

es en esT T O Tf oo oo S en ss m oo g 3 r^ en

T—t

es t -i§ i-H en es Tt es .

eobo

C

3

ää ää ; ;:; ;: : ii ; ;; ;: : jj-g-g-g :: :: : jj u: uâ j : : jj ii ll : • . « « « : . . S : : : . :. s . w

\J W W t j \J \J ^ 3

T3-a-a XI 73-a T3 T3 J3iSi3i2J2 —J2« S S S S S S S S

• •

°

_ ^¿Z ^ 2

yjáíác •E-E'fi

* • >Nfc*

•

* • •

' ' 2 'S 'S ' 3 *u t v 4

•

'' J *

tri

** * f l irfr^f^

co c *1 Ü^E^Ü^^ÜLo 1o o o o *" S '3 *n3 ^ " Ï Ï - ^ U A

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

58

Lam and Mirón

1950's, the peak of the baby boom, and the mid-1970's, the trough of the baby bust. The figures also demonstrate that the seasonal patterns are highly persistent; the basic timing of peaks and troughs, as well as the approximate magnitudes of the fluctuations, remain essentially constant over long periods. The actual timing of the monthly patterns in the two populations is difficult to see in these figures but will be shown in detail below. Table 1 presents more extensive evidence on the quantitative significance of seasonal fluctuations. The table shows, for a large sample of populations, the i?2's from regressions of detrended log births on monthly dummies, as well as the peak-to-trough amplitudes in the seasonal patterns. The table also reports the twelve estimated monthly coefficients for later reference. As shown in the table, the R2's regularly exceed 50 per cent and are as high as 80 per cent even in recent periods in highly developed populations. The peak-to-trough amplitudes in births reported in Table 1 are almost always greater than 10 per cent and are as high as 30 per cent in a number of modern, urban populations. Tests of statistical significance (not reported in the tables) reject the null hypothesis of no seasonality at the 1 per cent level in all cases. Thus, according to any reasonable measure, seasonal fluctuations are a dominant source of variation in births. GEOGRAPHICAL VARIATION IN BIRTH SEASONALITY

The summary statistics in Table 1 document the fact that seasonal fluctuations in births are quantitatively important. We turn now to an examination of the geographical variation in these seasonal patterns. The first characteristic we establish is that there is no simple

Social Biology

rule determining the seasonal pattern that occurs in a particular country, despite the presence of significant seasonal fluctuations in every country. We begin by considering the patterns in white births in three states representing different geographic regions of the United States, shown in Panel A of Figure 3. All of the states exhibit a September peak and an April-May trough, a pattern well established in previous studies of U.S. birth seasonality (Cowgill, 1966; Rosenberg, 1966; Macfarlane, 1970; Lyster, 1971; Seiver, 1985). The figure demonstrates a persistent regional difference in birth seasonality in the United States. The April-May trough is noticeably more pronounced in Georgia than in California and New York, and the overall magnitude of birth seasonality is larger in Georgia. As documented in previous studies of U.S. birth seasonality, the Georgia pattern shown here is typical of the southern United States. The R2 statistics imply that seasonal fluctuations explain around 40 per cent of the nontrend variation in births in the states shown, with peak-to-trough amplitudes ranging from 10 per cent to 25 per cent. Panel B of Figure 3 shows the seasonal patterns in Canada and England. The Canada and England patterns are similar to the U.S. patterns in the presence of a September peak followed by a reduction in births in October through January. They differ from the U.S. pattern in the spring months, however, with no evidence of the spring trough that is so pronounced in the southern United States. England exhibits a noticeable March peak in births, with a peak-totrough amplitude of about 13 per cent in the 1948-83 period. The pattern exhibited by England is similar to that of many continental European populations. Panels C and D of

59

Seasonality of Births

Vol. 38, No. 1-2

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

A. United States. 1948-1986

1

2

3

•

5

O California

«

7

S

• Georgia

B. Canada and England

« B

10

11

12

1

C. Denmark and Sweden

1

2

3

4

5

8

7

G Denmark, 1940-86

8

2

3

1

2

3

4

5

6

9

10

11

12

* Sweden, 1948-87

7

8

9

5

S

7

S

B

10

11

12

* England, 1948-83

D. Netherlands and West Germany

1

2

3

4

5

8

7

O Netherlande, 19S1 - 8 3

S

S

10

It

»

* Wast Germany, 1948-67

F. Italy and Spain

E. France and Luxembourg

G Franca. 1959 - 83

4

©Canada. 1948-76

New York

10

11

12

• Luxembourg, 1948-82

1

2

3

4

5

8

0 Italy. 1949-81

7

8

9

10

11

12

• Spain. 1949-82

FIG. 3.—Patterns of birth seasonality, North America and Europe. Percentage deviations from trend in births by month of birth.

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

60

Lam and Mirón

Figure 3 present patterns for the northern European populations of Denmark, Sweden, Netherlands, and West Germany for the post-World War II period. The "European pattern" consists of a global spring peak, a local September peak, and a significant trough during the late fall and early winter. In several of these countries, the change from peak to trough is as high as 30 per cent, with the seasonal dummies explaining as much as 80 per cent of the nontrend variation in births. The pattern seen here is markedly different from that in the United States, particularly the spring peak in Europe as opposed to the spring trough in the United States. The patterns do have the September peak in common, as well as some similarity with respect to the fall/winter. Panels E and F of Figure 3 show patterns for the central and southern European countries of Luxembourg, France, Spain, and Italy. These countries exhibit less dramatic seasonally than the northern European countries. A number of features of the "European pattern" persist, however, including the local September peak and the October through January trough. Figure 4 shows seasonal patterns for a number of populations outside of North America and Europe. Panels A and B show the seasonal pattern for five regions of India. Delhi and Punjab are the most northern of the Indian states included here, with Delhi at roughly the same latitude as Florida and Punjab at roughly the same latitude as Georgia. Maharashtra and West Bengal are further south, at roughly the same latitude as central Mexico. Kerala is in the far south, at latitudes corresponding to Central America. The raw birth series for Kerala and West Bengal show much less regular seasonal patterns than do the other three states, suggesting the

Social Biology

possibility of significant measurement error. Since we do not have any specific reason to exclude these two series, however, we present the seasonal patterns but suggest that they be interpreted with caution. Kosambi and Raghavachari (1951) present evidence on birth seasonality in India during the pre-WWII period. The patterns for the three regions shown in Panel A—Delhi, Maharashtra, and Punjab—are strikingly similar to patterns for southern regions of the United States. Delhi, the region of India with the most extreme amplitude in seasonality, has an April-May trough and a September peak. As seen in Table 1, the peak-to-trough amplitude and the R2 for the regression for Delhi are much higher than those for other populations in Figures 3 and 4. The two other regions shown in Panel B, Kerala and West Bengal, display somewhat different seasonal patterns, although West Bengal does exhibit a local September peak, a feature frequently observed in the seasonal patterns presented here. Panel C shows the seasonal birth patterns for two regions of Japan, the Tokyo and Kagoshima prefectures. Tokyo is at a latitude close to that of Washington, D.C., while Kagoshima is at a latitude close to that of Georgia. Seasonal fluctuations in Japan are closer in magnitude to those of the North American and European populations than to those in India, and they show some similarity to the North American pattern of a September peak followed by a November trough. Panel D of the figure shows the seasonal birth pattern for Israel. Israel's pattern is remarkably similar to that in the southern United States, exhibiting an April trough and September peak, with an amplitude of 15 per cent.

Vol. 38, No. 1-2

Seasonality of Births

A. India - Delhi, Mahar., Punjab

61

B. India- Kerala, West Bengal

25

f

15

5 -B

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

-15

-!tt 1

2

3

4

S

G Delhi 59-69

6

7

S

S

1

• Mahar. 60-79

0

1 1 1 2

s Punjab 67-79

1

2

3

4

1

2

3

4

6

6

7

8

0

6

7

6

0

10

11

12

«Went Bengal, 1959-79

D. Israel

C. Japan - Kagoshirna, Tokyo

OKagoshlma, 1969-83

5

© Kerala, 1959-77

10

11

12

* Tokyo, 1969-63

F. South Africa. 1953-77

E. Australia and New Zealand

15 10 6 -

•

—

~

*

"V-"" -5 -10 -15 20 1

2

3

4

6

0Australia. 1963-85

6

7

6

9

10

11

12

* New Zealand, 1960-82

1

2

3

4

5

e Black

6

7

S

B

10

11

12

»White

FIG. 4.—Birth seasonality outside of North America and Europe. Percentage deviations from trend in births by month of birth.

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

62

Lam and Mirón

In Panels E and F of Figure 4 we show the seasonal birth patterns for the southern hemisphere countries of Australia, New Zealand, and South Africa. Although comparisons of seasonal patterns across hemispheres are appealing to test a number of hypotheses about birth seasonality, such comparisons are in practice inconclusive. The pattern shown for Australia, consisting of a global March peak, a local September peak, and a NovemberDecember trough, is surprisingly similar to the pattern for England in Figure 3. Earlier analyses of birth seasonality in Australia, however, identify a September global peak. Rosenberg (1966), for example, presents a seasonal pattern for South Australia for the period 1957-59 that is remarkably similar to the United States pattern in both timing and magnitude. Mathers and Harris (1983) analyze three-year periods from 1962 to 1979 and conclude that the Australian pattern shifts from a September peak to a March peak (see also Macfarlane and Spalding, 1960; Lyster, 1979; and Parker, 1978,1979). The change in pattern is primarily a change in relative magnitudes. The March and September local peaks shown in our estimates in Figure 3 appear in virtually all periods in Australia, with the September peak being more predominant in earlier periods. The pattern for New Zealand, also shown in Panel E of Figure 3, demonstrates a seasonal pattern similar in shape to that of Australia, but with the September peak significantly more pronounced. The New Zealand pattern, with the sharp September peak and April-May trough, displays the key features of the U.S. pattern. Panel F shows the seasonal birth pattern by racial group for South Africa.

Social Biology

South African blacks in the period 1953-77 exhibit a pattern quite similar to the pattern in the southern United States, with a May trough and a September peak. The pattern for South African whites is smaller in amplitude and somewhat different in shape, although whites display a September local peak and December trough similar to the pattern for blacks. Cowgill (1965) and Crook and Dyson (1980) document a September peak for all races in South Africa using data for earlier periods, while Dyson and Crook (1981) suggest that the pattern for whites changes in more recent periods to a pattern with a March peak. Their comparisons across time are based on only three-year periods, however. These periods may be too short to establish systematic seasonal patterns. The stylized fact established by the geographical comparisons in Figures 3 and 4 is that there is no simple rule determining which population displays a particular seasonal pattern of births. The "U.S." pattern and the "European" pattern show up in many populations, but not according to any simple scheme. The September global or local peak does appear in numerous cases, across a wide variety of geographical and cultural settings. There is no evidence that seasonal patterns are consistent within hemisphere or simply reversed across northern and southern hemispheres. CHANGES OVER TIME IN BIRTH SEASONALITY

A second important characteristic of the cross-population variation in seasonal patterns is the stability of these patterns over time. We begin by examining what is surely the longest time series of monthly births in existence, the 300-year series constructed by Wrigley

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonally of Births

and Schofield (1981) for pre-industrial England. As mentioned above, this is the only data source we use that is not based directly on vital statistics, so a number of caveats are in order. The series used here is exactly as published in Wrigley and Schofield's Appendix A2.4, as constructed from parish reconstitutions. The time between birth and baptism, and possible changes in this interval across seasons and across time, may confound the seasonal pattern, in addition to distorting the secular changes in this pattern (see Wrigley and Schofield, 1981, for a discussion of some of these issues). We find it unlikely that the dramatic decrease in seasonality discussed below can be explained entirely by these data problems, but the Wrigley-Schofield monthly birth series must be interpreted with caution. Figure 5 shows the seasonal birth patterns for the Wrigley-Schofield series for three periods. The figures show a dramatic decline in the amplitude of the seasonal patterns, with the peak-totrough difference of 48 per cent in the 1539-1637 period dropping to 25 per cent in the 1737-1836 period. Knodel and Wilson (1981) document a similar secular decline in birth seasonality over a 150-year-period in eighteenth- and nineteenth-century German villages. As shown in Panel B of Figure 5, however, there is still substantial seasonality in births in England in the post-WWII period. The timing of the seasonal pattern after WWII is remarkably similar to that in earlier periods, with a late winter peak and a summer trough. Figure 5 also plots the seasonal patterns in births for a series of periods in the twentieth century in Finland, Canada, Luxembourg, and Sweden. Given the dramatic economic and social changes in these countries during the

63

century, the most surprising feature of these patterns is their relative stability through time. Luxembourg shows some evidence of a decline in the amplitude of seasonal fluctuations, in the form of a reduction in the March peak in births. Canada shows very little change in its seasonal birth pattern from the 1926-38 period to the 1963-76 period. Luxembourg and Finland show some evidence of changes in seasonal patterns, but also show considerable stability in the overall amplitude and in particular features such as the local September peak and the October-December trough. Most surprising of all is the increase in seaonality in Sweden during the twentieth century. While the basic shape of the pattern remains similar, the peak-totrough amplitude increases from 17 per cent in the 1921-38 period to 31 per cent in the 1969-87 period. Changes over time for the United States are illustrated in Figure 6. The figure compares the seasonal pattern by racial group for Georgia and New York for two separate periods, 1948-68 and 1969-86. (U.S. vital statistics are classified by white and nonwhite prior to 1969, and for white and black beginning in 1969. The change in classification is not especially critical in states such as Georgia and New York where blacks are by far the predominant component of nonwhite births.) The most significant change over time is a substantial decline in the amplitude of birth seasonality for whites in Georgia. Seasonality for blacks in the South, and for both blacks and whites in the North, changes very little in either timing or amplitude across the two periods. The decline in birth seasonality for whites in the U.S. South has been documented in previous research by Querec and Spratley (1978) and Seiver (1985).

B. England, Vital Statistics Series

A. England, Wrigley-Schofield Series

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Social Biology

Lam and Mirón

64

1

2

3

4

8

01539-1637

(

7

8

«

10

11

12

«1638-173« B 1737-1838

D. Luxembourg

C. Canada

1

2

3

4

01828-1938

6

B

7

8

»1943-1962

9

10

B

1 1 1 2

1963-1976

E. Finland

1 2 3 4 5 0 7 8 S 10 11 12 01928-1938 «1948-1968 B1969-1986

1 2 3 4 5 6 7 8 S 10 11 12 G1919-1938 «1948-1968 a 1969-1982

F. Sweden

2 3 4 01921-1938

5 6 7 8 « 10 11 12 «1948-1968 H1969-1987

FIG. 5.—Changes in birth seasonality over time. Percentage deviations from trend in births by month of birth.

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonality of Births

. Georgia Non-white and White, 1948-68

B. Georgia Black and White. 1969-86

. New York Non-white and White, 1948-68

D. New York Black and White, 1969-86

1

2

3

4

6

6

7

GNon-wtirlo

6

0

10

11

65

12

* White

FIG. 6.—U.S. birth seasonality. Percentage deviations from trend in births by month of birth.

These secular changes in seasonal patterns indicate that although seasonality may be less important now than during the pre-industrial period, it has not disappeared in any population and has actually increased in one. Further, the timing of the seasonal patterns has remained essentially unchanged even in those populations where there have been changes in overall amplitude.

patterns for subpopulations that are potentially relevant to interpreting the determinants of birth seasonality. Figure 6, analyzed above with respect to changes over time in seasonality in the United States, also demonstrates the existence of substantial differences in the magnitude of birth seasonality for U.S. whites and nonwhites. In Georgia there is a marked decrease in the magnitude of the spring trough over time for whites VARIATIONS IN BIRTH SEASONALITY but no obvious change in the pattern for ACROSS SUB-POPULATIONS blacks. In New York, however, the difVital statistics for some countries ference in the magnitude of this trough make it possible to estimate seasonal is clearly present and of approximately

66

A. United States, First and Second White Births, 1960-86

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Social Biology

Lam and Mirón

1

2

3

4

5

6

7

O First Birth«

8

0

10

11

• Second Birth«

C. England, Illegitimate and Legitimate Births, 1948-83

12

B. United States. First and Second Non-White Births. 1960-86

1

2

3

4

6

6

4

6

6

O BsgKlmata

1

2

3

4

S

6

7

G Illegitimate

8

B

1

0

8

9

10

11

12

• Second Birth«

D. Finland. Illegitimate and Legitimate Births. 1926-38

3

E. Sweden. Illegitimate and Legitimate Births, 1948-64

7

eFtrit Birth«

7

8

9

10

11

12

* Legitimate

F. Sweden, Rural and Urban Births. 1948-64

1 1 1 2

» Légitimais

FIG. 7.—Intrapopulation variation in patterns of birth seasonality. Percentage deviations from trend in births by month of birth.

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonality of Births

the same magnitude for both the early and later sample periods. In Lam and Miron (1987), we demonstrate that these results hold generally for states in the South and Northeast. Figure 7 presents seasonal patterns for a variety of additional subpopulations. Panels A and B contrast seasonal patterns for first births versus second births for whites and nonwhites in the United States. (Births by birth order are not available at the state level in published vital statistics data.) The seasonal patterns are quite similar for the two groups. There is some evidence of slightly more seasonality in first births for whites, but the difference is small and causes no change in the basic timing of peaks and troughs. Panels C, D, and E of Figure 7 contrast the seasonal patterns for legitimate and illegitimate births for England, Finland, and Sweden. For England the patterns are virtually identical in both timing and magnitude. For Finland the patterns are similar in the most pronounced features and have similar amplitudes. In Sweden the timing of peaks and troughs is the same for legitimate and illegitimate births, but illegitimate births exhibit a lower amplitude in seasonal fluctuations. Panel F of Figure 7 compares births in rural and urban Sweden during the post-WWII period. The striking feature of the rural-urban comparison for Sweden is the similarity in both the timing and amplitude of the seasonal fluctuations in the two regions. Results reported in Table 1 but not included in the graph indicate that the significant increase in the amplitude of Swedish birth seasonality during the twentieth century, documented above in Figure 5, is similar in rural and urban areas. For urban births, the peak-to-trough ampli-

67

tude rises from 14 per cent in the 192138 period to 26 per cent in the 1948-64 period, while for rural births the corresponding increase is from 18 per cent to 24 per cent. SUMMARY OF BASIC FACTS

We can summarize the facts presented above as follows: 1. Seasonality is a quantitatively important feature of the variation in births in populations covering a wide variety of geographical areas, historical periods, and cultural settings. 2. The presence of a particular seasonal pattern is not governed simply by the hemisphere in which that country resides. 3. There does not appear to be a consistent conclusion about whether the amount of seasonality increases or decreases over time. In some countries the amount decreases significantly; in many it remains stable; and in one (Sweden) it increases significantly. 4. The differences in seasonal patterns across urban/rural populations are relatively small. 5. The differences in the patterns of legitimate and illegitimate births are small, at least in Sweden, Finland, and England. Similarly, the differences by birth order, at least for the United States, are not quantitatively important. 6. Other comparisons across subpopulation, such as those by race or income class, provide conflicting results. DISCUSSION EXPLANATIONS OF BIRTH SEASONALITY

We turn now to discussing the proposed explanations of birth seasonality found in the literature. A number of the existing explanations are based on ex-

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

68

Lam and Mirón

amination of data for one population, and many of these hypotheses appear reasonable when confronted with evidence from only a few countries. Since alternative explanations of birth seasonality have implications for the crosscountry or cross-time period variation in seasonal patterns, however, it is useful to confront these explanations with the variety of seasonal patterns presented above. We show below that these facts do not by themselves eliminate any interesting hypothesis. The results do, however, place significant limits on how important various explanations might be for an overall understanding of birth seasonality, and they suggest avenues that future research should follow in order to pursue these explanations further. Since the number of proposed explanations of birth seasonality in the existing literature is large and diverse, it is useful to have a simple framework within which to discuss proposed explanations. We organize our discussion of the literature around the possible exogenous determinants of birth seasonality, namely, the weather, the agricultural cycle, economic variables, holidays, and the marriage rate. It is of course possible that the seasonality in some of these variables is a response to the seasonality in births. For example, couples may choose to get married nine months before the month in which they would like to have a birth. While we recognize the possibility of such endogeneities, we regard them as sufficiently implausible that we do not discuss them further in this paper. We emphasize wherever possible the behavioral or biological mechanisms through which these variables may be operating. Lam and Miron (1987) present a simple, formal model of birth seasonality.

Social Biology WEATHER

There are a number of possible mechanisms through which the seasonality of the weather might determine the seasonality of births. On the behavioral side, couples may desire births in spring months because this improves the health and survival probabilities of the child or fetus. Women may desire spring births because it is uncomfortable to be pregnant in the summer (Rodgers and Udry, 1988). In addition, couples may choose to engage in intercourse more often in certain seasons because of the weather. In the first two cases, it is the expected variation in the weather that is crucial, since couples' frequency of intercourse is determined before knowing the weather at the time of the birth. In the third case, the actual value of the weather in the month of intercourse might be important. On the biological side, seasonal fluctuations in temperature or other aspects of the weather may affect fecundity through a number of mechanisms that are outlined below. Previous literature on the seasonality of births provides some evidence supporting weather-based explanations. Indirect evidence is provided by comparisons of seasonal patterns across socioeconomic groups. Greater seasonality for lower-income classes could be interpreted as evidence supporting weather-induced seasonality, since high-income groups may control their environment more completely than lowincome groups. The most recent analysis of socioeconomic differentials in seasonality is by Kestenbaum (1987), who uses the 1980 U.S. census to identify the quarterly pattern in births in years immediately prior to the census, controlling for parental income. Consistent with a number of previous studies for

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonally of Births

69

the U.S., Kestenbaum finds somewhat April-May trough in births is based on a greater seasonality among lower- regression of the time trend in the magincome groups. Based on characteristics nitude of the May seasonal effect for of parents at the time of the 1980 census, each state between 1960 and 1970 on the April-June births in 1977-79 were 6 per increase in air conditioning in the state cent below the annual average for those between the 1960 and 1970 censuses. with less than high-school education, Seiver's interesting results provide supbut were only 3 per cent below the an- port for the hypothesis that summer nual average for those with college edu- heat reduces conceptions and thus partication. Kestenbaum's results are subject ally explain the April-May trough in to the criticism that income and educa- births. Seiver's results do not explain the tion in his sample are highly correlated August-September peak in births, the with residence in northern versus south- other dominant feature of the U.S. seaern states. His results may therefore sonality pattern. Seiver (1989) tests the simply reflect the large north-south dif- role of weather more directly by estiferentials in seasonality, as seen in Fig- mating the effect of summer temperaure 3, rather than provide independent ture extremes on births nine months evidence of socioeconomic differentials. later. His results indicate that increases Earlier studies of socioeconomic dif- in summer temperatures have a direct ferentials in birth seasonality are some- negative effect on births. what inconclusive, being based on small geographical areas and/or short time periods. Pasamanick et al. (1959,1960) report more seasonality in low-income groups than in high-income groups in Baltimore, although reexamination by Zelnik (1969) indicates no significant differences between income groups. A replication of the Baltimore study by Chaudhury (1972) supports the finding of greater seasonality among lowerincome groups, and Warren and Tyler (1979) find similar differences based on birth records for a county in Georgia. In contrast to these findings of greater seasonality among low-income groups in the United States, James (1971), comparing birth seasonality across social classes in England, finds less seasonality among low-income groups. His results are based on comparisons for only a single year's vital statistics data, however. The role of weather in seasonality in the United States is examined indirectly by Seiver (1985). His test of the hypothesis that summer heat explains the

In addition to Seiver's (1989) use of monthly weather data for the United States, the effects of the weather on fertility have been tested using direct weather variables by Lee (1981) and Richards (1983), although they do not consider seasonality per se. Lee uses over three hundred years (1541-1871) of monthly, seasonally adjusted data for England to determine the effects of temperature and rainfall on births seven to eleven months later. He finds that temperature extremes reduce future fertility rates, mainly through intrauterine mortality effects. The estimates are statistically significant, but quantitatively small. Richards estimates the effect of temperature extremes on annual births for France for the period 1740-1909. Her point estimates are consistent with the hypothesis that temperature extremes reduce fertility nine months later, but the estimates are never statistically significant. Chang et al. (1963), using data for Hong Kong, report a strong negative correlation between the

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

70

Lam and Mirón

seasonal pattern in temperature and the seasonal pattern of conceptions. Their results are consistent with a weatherbased explanation of birth seasonality, but they fit other explanations as well. In particular, the seasonal pattern in marriages matches the seasonal pattern in conceptions quite well. Recent work by Becker et al. (1986) may suggest an important effect of the weather on birth seasonality in Matlab, Bangladesh. Their study finds that the large seasonal variation in fecundability can be only partially explained by the seasonal variation in the frequency of intercourse. In particular, there is a peak in frequency of intercourse in September, the period of lowest fecundability. Since September is the month with highest mean monthly temperature, an effect of temperature on spermatogenesis or the fetal loss rate appears likely. As emphasized by Becker et al. (1986), however, further investigation is required to determine the precise mechanisms through which temperature affects fecundability. The most thorough examination of the role of weather in producing the seasonality of births is that by Roenneberg and Aschoff (1989ft), who find that temperature and latitude (which they interpret as a proxy for photoperiod) explain much of the variation in seasonal patterns across countries. They note, however, that the effects of temperature and latitude are reversed across America and the rest of the world. Their work does not, therefore, explain the differences in seasonal patterns between the United States and Western Europe, which arguably constitute some of the most intriguing puzzles. The differences in seasonal patterns that they fail to explain coincide exactly with those left unexplained by Lam and Miron (1990). They find significant effects of summer

Social Biology

heat extremes in reducing summer conceptions, but they do not explain the significant increases in summer conceptions that occur in much of Europe. The biomédical literature contains some evidence that weather affects the biological probability of conception, as well as some evidence of seasonality in this probability, which may reflect the weather. Levine et al. (1988) show that semen quality in a sample of 1,235 men deteriorates significantly from winter to summer in New Orleans, with the size of the deterioration greatest in those occupations most exposed to external temperature. Similarly, Levine et al. (1990) find that several measures of semen quality deteriorate from winter to summer in a sample of 131 men who work outdoors in San Antonio, Texas, although they find no correlation between the magnitude of the deterioration and the number of hours spent without airconditioning. Zorgniotti and Sealfon (1988) find significantly higher scrotal temperatures in subfertile than normospermic men. Studies of small numbers of subj ects suggest monthly variations in male hormones related to sexual activity (Reinberg, 1974; Reinberg et al, 1978), without explaining the sources of the variations directly. Research based on a sample of males in Houston, Texas, indicates significant seasonal variation in sperm count, with peaks in February and March and a trough in September (Tjoaetal., 1982). This pattern of peaks and troughs in sperm count implies a peak in births in November and December and a trough in June, predictions that differ by one to two months from the seasonal pattern in births in Texas. Seasonal variations in menstrual cycles and menarche have also been documented (Sundararaj et al., 1978; Brundtland and Liestol, 1982), suggesting possible physiological explanations

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonally of Births

of seasonality on the female side as well. Results for a sample of women in Minnesota show some shortening of menstrual cycles during spring and summer months (Sundararaj et al., 1978). Again no direct explanations of the seasonal variations in menstruation are provided, although Sundararaj et al. speculate that the effects might result from seasonal changes in physical activity or external temperature. The weather may also operate through effects on intrauterine mortality. Holmes (1968), Macfarlane (1970), and Tromp (1963), for example, discuss the possible relationship between temperature extremes, intrauterine mortality, and birth seasonality. The evidence is mixed on whether such an effect is empirically important (Slatis and DeCloux, 1967; Huntington, 1938; McDonald, 1971; Warren et al., 1980). Research on animal populations suggests that several factors, especially photoperiod, cause conceptions to be timed so that births are concentrated in the spring, when survival probabilities are highest (Karsch et al., 1984). Although the relationship between photoperiod and seasonal breeding in animals appears to be well established, there has been little research analyzing effects of photoperiod on human reproduction. Ehrenkranz (1983a, 1983Ö) argues that photoperiod variations may explain seasonal variation in conceptions among Eskimo populations, but his results are based on small samples and provide only indirect evidence at best of an effect of photoperiod on human reproduction. Roenneberg and Aschoff (1989&) argue for an important effect of photoperiod using latitude as a proxy. As mentioned above, their results are suggestive but do not explain some of the most striking puzzles in the data.

71

The evidence in the existing literature is therefore inconclusive concerning the possible role of the weather. The evidence that we have provided above on cross-population comparisons presents a clear challenge to any weatherbased hypothesis. According to the simplest possible model of the relation between weather and either behavior or biology, countries in the northern hemisphere should display similar seasonal patterns, and these patterns should be six months reversed from the patterns displayed in the southern hemisphere. Yet, as we have documented above, there is little consistency to the patterns across countries or hemispheres. The simplest case of a single northern hemisphere pattern that is reversed by six months in the southern hemisphere clearly does not hold, even across countries that are culturally and economically quite similar. The significant differences between the United States and European patterns, and the striking similarity of the United States and New Zealand patterns, are a clear challenge to any explanation of birth seasonality based only on seasonal weather patterns. The difficulties involved in explaining the cross-population differences in birth seasonality by means of differences in weather seasonality are illustrated clearly in Figure 8. Panel A shows the seasonal pattern in births in Georgia, Minnesota, New York, and Sweden, while Panel B shows monthly average temperature for the same locations. Although the basic shape of the seasonal patterns in temperature are the same, the differences in birth seasonals are dramatic. It seems likely that no explanation based solely on weather effects can reconcile these data.

72

Lam and Mirón

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

A. Percentage Deviations from Trend in Birthf by Month of Birth

©Gaorgta. 1 9 4 8 - 8 6 S New Ybrk, 1 8 4 8 - 8 6

Social Biology

B. Mean Temperature in Degrees Farenheit by Month

w 11 U m Mlmnota. 1 9 4 8 - 6 6 á Swadan, 1 0 4 8 - 8 7

eOaorgla, 1940-82 B Newtork. 1940-82

10 n 12 • Minnesota. 1940-82 & 8woden. 1948-83

C. Percentage Deviations from Trend in Marriages by Month of Marriage

O Georgia, 1863-84 E> Sweden, 1861-88

-84

FIG. 8.—Seasonally in births, temperature, and marriages, Georgia, Minnesota, New York, and Sweden.

The evidence presented above does not completely rule out the effects of the weather. The argument that countries in the same hemisphere should have similar seasonal patterns obviously relies on the assumption that countries within the same hemisphere have similar weather. While Figure 8 shows that this assumption is correct regarding the basic timing of warm months and cold months, it may not be accurate with respect to the dimensions of the weather that determine birth outcomes. For example, it may be that the weather is only impor-

tant when it reaches extreme values, such as the summertime heat experienced by the southern United States. If this is the case, then the weather might have quite different effects in Georgia than in Sweden, even though summer is the warmest season in both locations. AGRICULTURE

The second variable that is often proposed as an important determinant of the seasonal fluctuations in births is the agricultural cycle. The harvest cycle might operate on birth outcomes

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonality of Births

through a number of mechanisms, and there is some evidence in the literature to support each of these mechanisms. Nurge (1970) hypothesizes a relationship between labor demand and the desired timing of births and finds corroborating evidence in data from a German peasant village. More recently, Levy (1986) finds patterns of birth seasonality in contemporary rural Egypt that are consistent with attempts to avoid births in the periods of peak labor demand. Mosher (1979) argues that seasonal variation in nutrition explains much of the seasonal variation in births in Taiwan during the 1926-76 period. The agricultural cycle may affect the frequency of intercourse by raising its opportunity cost in periods of peak labor demand, including as an extreme case spousal separation due to seasonal labor migration (Chen et a l , 1974; van de Walle, 1975; Menken, 1979; Massey and Mullan, 1984). Spencer et al. (1976) and Spencer and Hum (1977) argue that decreases in workload during periods of low agricultural labor demand lead to increased conceptions in several populations. Knodel and Wilson (1981) report evidence of a strong seasonal pattern in births in eighteenth- and nineteenthcentury German villages. The most pronounced feature of the pattern is an early summer trough which the authors argue is consistent with reduced conceptions during the harvest period of August through November. The agricultural cycle is a plausible hypothesis to explain birth seasonality, and it may well have played an important role in pre-industrial societies. In particular, the dramatic decline in the amplitude of seasonal birth fluctuations in pre-industrial England probably reflects the declining importance of the agricultural sector. In addition, the agri-

73

cultural cycle is obviously a key determinant of birth seasonality in some current less-developed, highly agricultural societies such as Matlab, Bangladesh (Becker, 1981). The fact that the seasonal pattern in pre-industrial England emerges consistently in northern European countries well into the twentieth century, however, suggests that the agricultural explanation is far from the entire story. More importantly, the increasing seasonality in Sweden, combined with the similarity of rural and urban patterns, makes it highly implausible that this is the main effect in modern populations. ECONOMIC VARIABLES

In addition to the possible role of the agricultural cycle, a number of other economic variables may be important determinants of the seasonality of births. If labor force opportunities for women are seasonal, they may attempt to time pregnancies so that as little work time as possible is lost due to pregnancy and/or child care. Alternatively, seasonality in male labor force participation could affect the amount of contact between husbands and wives. There are large seasonals in economic activity in most economies, and these patterns turn out to be very similar around the world (Barsky and Miron, 1989; Beaulieu and Miron, 1990fl,è). The results presented in Figure 5 above provide suggestive evidence on the possible role of these other economic variables in producing the seasonality of births. It seems unlikely that seasonal variations in economic variables are the primary factor in determining the seasonality of births because of the marked absence of dramatic changes in the timing of seasonality over long periods. For the five long time se-

ries we consider (England, Finland, Sweden, Canada, and Luxembourg), we have data covering a transition from an almost entirely agricultural economy to a significantly industrial one. There is no reason to believe that the seasonality in agricultural and industrial activities is the same, so the stability in the timing of the patterns over time suggests an absence of strong economic effects. Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Social Biology

Lam and Mirón

74

HOLIDAYS

Increased leisure time due to holidays, and the availability of other activities that may compete with or complement sexual activity, could also lead to seasonal variations in conceptions and births. Of course, it may be difficult to distinguish the effects of seasonal patterns in holidays, economic activity, and the weather, since the seasonality in economic activity and holidays may be determined simultaneously, with both of these possibly influenced by seasonal weather patterns. Casual observation, however, suggests that the winter holidays associated with Christmas, the New Year, and possibly Hannukah are important determinants of leisure time in a substantial fraction of the world, so evidence that births or conceptions are concentrated in December would suggest one particular holiday effect. Such a "Christmas effect" has been mentioned frequently in discussions of the September peak in U.S. births (e.g., Rosenberg, 1966) and is cited by Wrigley and Schofield (1981) as a possible explanation for a persistent September local peak in English births. Calot (1981) emphasizes August vacations as the reason for the strong May peak in births in France, and James (1971) argues that increased leisure time in holiday periods may explain his finding of greater seasonality among higher-income groups in England.

A number of features of the crosspopulation comparisons shed light on the hypothesis that holidays affect the seasonal pattern in births. The most noticeable is the evidence in favor of a Christmas effect on the conception rate. In almost every Christian country, in either hemisphere, there is at least a local September peak in births, consistent with increased conceptions during the Christmas holiday season. The persistent September peak is one of the intriguing recurring patterns across countries. It has no obvious explanation in terms of weather, especially since it occurs in both hemispheres and at all latitudes. The hypothesis that it is attributable to a Christmas holiday effect, however, must confront the presence of a September peak in the non-Christian countries of Israel and India. One possibility is that the increase in conceptions around Christmas is due to an increase in leisure time that occurs in all countries independent of religion. The other regular pattern in the data that may reflect the timing of holidays is the persistent spring peak in European countries, consistent with the hypothesis that there is increased sexual activity during the leisure time associated with summer holiday periods. The explanation of Sweden's spring peak as the result of summer holidays is consistent with the surprising secular increase in the amplitude of Sweden's spring peak over recent decades, an increase that could result from increased leisure time durig the summer in response to rising incomes. The data can be little more than suggestive of the role of summer holidays, however, in the absence of more direct tests. MARRIAGES

The possible effect of seasonal fluctuations in marriage rates on birth sea-

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

Vol. 38, No. 1-2

Seasonally of Births

sonality has been considered by a number of researchers, with mixed results. Rosenberg (1966) finds little effect of marriage seasonality on birth seasonality in the United States based on the large divergence between the seasonal pattern in marriages, which is dominated by a large peak in June, and the seasonal pattern in births, which implies below-average conceptions in June and July. Rosenberg also notes that legitimate and illegitimate births display similar seasonal patterns, based on data for the single year of 1963. Rosenberg's skepticism over the influence of marriage seasonality on birth seasonality has been repeated by other researchers. Mathers and Harris (1983), for example, conclude that marriage seasonality has little effect on birth seasonality in Australia because of the similarity between the seasonal patterns in legitimate and illegitimate births. A recent noteworthy exception to the view that marriage is unimportant in influencing birth seasonality is Prioux (1988), who reports a significant peak in conceptions for first births in October in Italy, based on data for the period 196079. Prioux attributes this peak to a peak in marriages in September-October. Higher-order births do not exhibit the same October peak in conceptions in Italy. Prioux argues that the overall level of birth seasonality increased in Italy during this period as first births became a higher fraction of all births. Our own evidence presented above also provides a mixed assessment of the possible role of marriages. Comparisons of the seasonal patterns for legitimate and illegitimate births (Figure 7) give little support to an important role for marriage seasonality, since the major peaks and troughs in the seasonal birth pattern are the same for legitimate and illegitimate births. In England, the patterns for

75

legitimate and illegitimate births are virtually identical. Likewise, the similarity of seasonal birth patterns by birth order in the United States (Figure 7, Panels A and B) raises serious difficulties for the marriage cycle as an important determinant of birth seasonality. Seasonal patterns in marriages for three populations, Sweden, Georgia, and New York, are presented in Panel C of Figure 8. The change of scale compared to the graphs for birth seasonality is important to note, indicating the much higher magnitude of marriage seasonality. Sweden has a peak-to-trough amplitude of almost 150 per cent, while the states of Georgia and New York have amplitudes of over 60 per cent. All three patterns indicate large June peaks in marriages. If this marriage peak had a large effect on birth seasonality, it would presumably show up as an increase in births in March. Looking back at the seasonal birth patterns in Panel A, we do not see a sharp March peak in births in any of the populations, although there is a small local peak in births in March in New York. The April peak in births in Sweden could be partially influenced by the June peak in marriages, although we have seen that illegitimate births display a seasonal pattern virtually identical to that shown in Panel A. All three patterns indicate large June peaks in marriages. If this marriage peak had a large effect on birth seasonality, it would presumably show up as an increase in births in March. Looking back at the seasonal birth patterns in Panel A, we do not see a sharp March peak in births in any of the populations, although there is a small local peak in births in March in New York. The April peak in births in Sweden could be partially influenced by the June peak in marriages, although we have seen that ille-

76

Lam and Mirón

Social Biology

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

gitimate births display a seasonal pattern virtually identical to that shown in Panel A.

account for multivariate explanations. Our results suggest that there may be high returns to further research on birth seasonality and its underlying determiCONCLUSIONS nants. The two effects that appear to be most consistent with observed seasonal The empirical results in this paper patterns, i.e., seasonal fluctuations in present a set of basic stylized facts about weather and seasonal fluctuations in leithe seasonality of births. We show that sure time due to holidays, both raise births are highly seasonal in all human provocative issues. It is well worth seepopulations, even for very recent periing whether what appears to be a relaods in highly industrialized low-fertility tively large effect of summer heat in repopulations. The timing of the seasonal ducing fertility holds up to direct tests patterns, however, differs widely across using monthly weather data (Lam and populations. Although a large literature Miron, 1990). It is not clear whether this exists on birth seasonality, the magnieffect is due to behavioral or biological tude and persistence of seasonal fluctuaeffects, and further research is clearly tions in births continue to be important called for on the short-run relationship empirical puzzles in demography. The between temperature and fertility in fact that births in April are 31 per cent modern populations. Similarly, the nogreater than births in December in contion that holidays are associated with temporary urban Sweden, for example, nontrivial increases in conceptions in is a dramatic result that begs for an exhighly contracepting low-fertility popuplanation, especially in light of our findlations also poses a challenge to our uning that the amplitude of this seasonal derstanding of modern fertility behavcycle in Sweden has increased during the ior. It is important to determine whether twentieth century. this apparent feature of the seasonal This paper has surveyed possible ex- patterns stands up to more direct tests planations of the seasonality of births and to examine the specific behavior and considered whether those explana- that may produce it. tions can rationalize the basic stylized facts about birth seasonality. We conclude that existing evidence places some ACKNOWLEDGMENTS limits on the kinds of explanations that This paper has benefited from discussions may be important, but it does not deci- with Al Hermalin, Barbara Anderson, Robsively either rule out or support any in- ert Barsky, Severin Borenstein, Roger Gorteresting hypothesis. In order to make don, Richard Levine, Gary Solon, and additional progress in understanding the James Wood. Excellent research assistance determinants of birth seasonality, we was provided by Shubha Ghosh, Jon Tinand Todd Clark. Financial support was believe it is necessary to use data on var- berg, provided by the National Institute for Child iables other than births, to employ more Health and Human Development, Grant disaggregated data sets, and to explicitly No. 1-R01-HD22141. REFERENCES ANDERSON, B. A., and B. D. SILVER. 1988.

The

effects of the registration system on the seasonality of births: The case of the Soviet Union. Pop. Stud. 42:303-320.

BARSKY, R. B., and J. A. MIRON. 1989.

Sea-

sonal cycles and business cycles. J. Polit. Econ. 97:503-534. BEAULIEU, J. J., and J. A. MIRON. 1990a. Sea-

Vol. 38, No. 1-2

Seasonally of Births

sonality in U.S. manufacturing. NBER WP #3450. _____. 1990b. A cross-country comparison of seasonal cycles and business cycles. NBER WP #3459. BECKER, S. 1981. Seasonality of fertility in Matlab, Bangladesh. J. Biol. Sci. 13:97105.

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

BECKER, S., A. CHOWDHURY, and H. LERIDON.

77

Two findings from the decennial census. Soc. Biol. 34:244-248. KEVAN, S. M. 1979. Season of life-Season of death. Soc. Sci. Med. 13D:227-232. KNODEL, J., and C. WILSON. 1981. The secular

increase in fecundity in German village populations: An analysis of reproductive histories of couples married, 1750-1899. Pop. Stud. 35:53-84.

1986. Seasonal patterns of reproduction in Matlab, Bangladesh. Pop. Stud. 40:457472.

KOSAMBI, D. D., and S. RAGHAVACHARI. 1951.

BRUNDTLAND, G. H., and K. LIESTOL. 1982.

LAM, D. A., and J. A. MIRON. 1987. The sea-

Seasonal variations in menarche in Oslo. Ann. of Hum. Biol. 9:35-43. CALOT, G. 1981. L'Observation de la fécondité a court et moyen terme. Population 36:940. CHANG, K., S. CHAN, W. LOW, and C. No.

1963. Climate and conception rates in Hong Kong. Hum. Biol. 35:366-375. CHAUDHURY, R. H. 1972. Socioeconomic and

seasonal variations in births: A replication. Soc. Biol. 19:65-68. CHEN, L. C., S. AHMED, M. GESCHE, and

Seasonal variation in the Indian birth rate. Eugenics 16:165-191. sonality of births in human populations. Research Rep. #87-114, Population Studies Center, University of Michigan. _____. 1990. Temperature and the seasonality of births. In A. Zorgniotti (ed.), Temperature and the testis: Proceedings of a Conference. Plenum Press, New York. LEE, R. D. 1981. Short-term variation: Vital rates, prices, and weather, p. 356-401. In E. A. Wrigley and R. Schofield (eds.), The population history of England, 1541-1871: A reconstitution: Harvard Univ. Press, Cambridge.

W. H. MOSLEY. 1974. A prospective study of birth interval dynamics in rural Bangla- LEVINE, R . J . , B. L. BORSDON, R. M. MATHEW, M. H. BROWN, J. M. STANLEY, desh. Pop. Stud. 28:277-298. and T. B. STARR. 1988. Deterioration of seCOWGILL, U. M. 1965. Season of birth in man: men quality during summer in New OrContemporary situation with special referleans. Fertil. Sterility 49:900-907. ence to Europe and the southern hemiLEVINE, R. J., R. M. MATHEW, C. B. CHEsphere. Ecology 47:614-623. NAULT, M. H. BROWN, M. E. HURTT, K. S. _____. 1966. The season of birth in man: The BENTLEY, K. L. MOHR, and P. K. WORKING. northern New World. Kroeber Anthropol. 1990. Differences in the quality of semen in Society Papers 35:1-21. outdoor workers during summer and winCROOK, N., and T. DYSON. 1980. Variations ter. N. Engl. J. Med. 323:12-16. saisonnières des événements en afrique du sud: Contraste entre les races. Population LEVY, V. 1986. Seasonal fertility cycles in rural Egypt: Behavioral and biological linkages. 35:691-697. Demography. 23:13-30. DYSON, T., and N. CROOK. 1981. Causes of seasonal fluctuations in vital events, p. 135- LYSTER, W. R. 1971. Three patterns of seasonality in American births. Amer. J. Obstet. 162. In R. Chambers et al. (eds.), Seasonal Gynecol. 110:1025-1028. dimensions to rural poverty. Frances Pinter, _____. 1979. New seasonal distribution of London. births in New South Wales. Med. J. AustraEHRENKRANZ, J. R. L. 1983a. A gland for all lia 2:150. seasons. Nat. Hist. 6:18-23. _____. 1983b. Seasonal breeding in humans: MACFARLANE, W. V. 1970. Seasonality of conception of human populations. BiometeorBirth records of the Labrador Eskimo. Ferology 4:167-182. til. Steril. 40:485-489. HOLMES, R. L. 1968. Reproduction and envi- MACFARLANE, W. V., and D. SPALDING. 1960. Seasonal conception rates in Australia. ronment. Norton, New York. Med. J. Australia 47:121-124. HUNTINGTON, E. 1938. Season of birth. Wiley, MASSEY, D. S., and B. P. MULLAN. 1984. A New York. demonstration of the effect of seasonal miJAMES, W. H. 1971. Social class and season of gration on fertility. Demography 21:501birth. J. Biosoc. Sci. 3:309-320. 517. KARSCH, F. J., E. L. BITTMAN, D. L. FOSTER, R. L. GOODMAN, S. J. LEGAN, and J. E. RO-

BINSON. 1984. Neuroendocrine basis of seasonal reproduction. Recent Progress in Hormone Research 40:185-232. KESTENBAUM, B. 1987. Seasonality of birth:

MATHERS, C. D., and R. S. HARRIS. 1983. Sea-

sonal distribution of births in Australia. Internat. J. Epidemiol. 12:326-331. MCDONALD, A. D. 1971. Seasonal distribution of abortions. Brit. J. Prev. Soc. Med.

78

Lam and Mirón

25:222-224. MENKEN, J. 1979. Seasonal migration and seasonal variation in fecundability: Effects on birth rates and birth intervals. Demography 16:103-119. MOSHER, S. W. 1979. Birth seasonally among peasant cultivators: The interrelationship of workload, diet, and fertility. Hum. Ecol. 7:151-181.

Downloaded by [University of Sussex Library] at 16:06 03 February 2015

NEWEY, W., and K. WEST. 1987. A simple, pos-

Social Biology

ROENNEBERG, TILL, and JURGEN ASCHOFF.

1989a. Annual rhythm of human reproduction: I. Biology, sociology, or both?. J. Biol. Rhythms, in press. _____. 1989b. Annual rhythm of human reproduction: II. Environmental correlations. J. Biol. Rhythms, in press. ROSENBERG, H. M. 1966. Seasonal variation of births, United States, 1933-63. National Center for Health Statistics, Washington, D.C. SEIVER, D. A. 1985. Trend and variation in the seasonality of United States fertility, 1947 to 1976. Demography 22:89-100. _____. 1989. Seasonality of fertility: New evidence. Pop. Environ. 10:245-257.

itive definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55:703-708. NURGE, E. 1970. Birth rate and work load. Amer. Anthropol. 72:1434-1439. PARKER, G. 1978. Season of birth in New South Wales. Med. J. Australia 2:563-566. SLATIS, H. M., and R. J. DECLOUX. 1967. Seasonal variation in stillbirth frequencies. _____. 1979. New seasonal distribution of Hum. Biol. 39:284-294. births in New South Wales. Med. J. Australia 2:424. SPENCER, B., D. HUM, and P. DEPREZ. 1976. PARKES, A. S. 1968. Seasonal variation in huSpectral analysis and the study of seasonal man sexual activity, p. 128-145. In J. M. fluctuations in historical demography. J. Thoday and A. S. Parkes (eds.), Genetic Europ. Econ. Hist. 5:171-190. and environmental influences on behavior. SPENCER, B., and D. HUM. 1977. Workload and Plenum Press, New York. seasonal variation in birthrates reconsidered. Amer. Anthropol. 79:911-912. _____. 1976. Patterns of sexuality and reproSUNDARARAJ, N . , M . CHERN, L . G A T E W O O D , L . duction. Oxford Univ. Press, London. PASAMANICK, B., S. DINITZ, and H. KNO-

BLOCH. 1959. Geographic and seasonal variations in births. Publ. Hlth. Rep. 74:285288. variations in birth rates. Milbank Mem. Fund Quart. 38:248-254. PRIOUX, F. 1988. Mouvement saisonnier des naissances: Influence du rang et de la legitimite dans quelques pays d'Europe occidentale. Population 43:587-610. QUEREC, L. J., and ERNELL SPRATELY. 1978.

Characteristics of births, United States, 1973-1975. Vital and Health Statistics Series 21, Number 30. National Center for Health Statistics, Washington, D.C. REINBERG, A. 1974. Aspects of circannual rhythms in man, p. 423-505. In E. T. Pengelley (ed.), Circannual clocks. Academic Press, New York. REINBERG, A., M. LAGOGUEY, F. CESSELIN, Y. Tourrou, J. LEGRAND, A. DELASSALLE, J. ANTREASSIAN, and A. LAGOGUEY. 1978. Or-

HICKMAN, and R. MCHUGH. 1978. Seasonal

behavior of human menstrual cycles: A biometric investigation. Hum. Biol. 50:15-31. TAKAHASHI, E. 1964. Seasonal variation of conception and suicide. Tohoku J. Exper. Med. 84:215-227. TJOA, W. S., M. SMOLENSKY, B. HSI, E. STEINBERGER, and K. SMITH. 1982. Circannual

rhythm in human sperm count revealed by serially independent sampling. Fertil. Steril. 38:454-459. TROMP, S. W. 1963. Medical biometeorology. Elsevier, Amsterdam. VAN DE WALLE, F. 1975. Migration and fertility in Ticino. Pop. Stud. 29:447-462. WARREN, C. W., and C. W. TYLER. 1979. So-

cial status and season of birth: A study of a metropolitan area in the southeastern United States. Soc. Biol. 26:275-288. WARREN, C. W., J. GOLD, C. W. TYLER, J. C.

SMITH, and A. L. PARIS. 1980. Seasonal vari-

ation in spontaneous abortions. Amer. J. Publ. Hlth. 70:1297-1299.

cadian and circannual rhythms in plasma hormones and other variables of five healthy young human males. Acta Endocrinol. 88:417-427. RICHARDS, T. 1983. Weather, nutrition, and the economy: Short-run fluctuations in births, deaths, and marriages, France 1740-1909. Demography 20:197-212.

population history of England, 1541-1871: A reconstitution. Harvard Univ. Press, Cambridge. ZELNIK, M. 1969. Socioeconomic and seasonal variations in births: A replication. Milbank Mem. Fund Quart. 47:159-165.

RODGERS, J. L., and J. R. UDRY. 1988. The

ZORGNIOTTI, A. W., and A. I. SEALFON. 1988.

season-of-birth paradox. Soc. Biol. 35:171-185.

Measurement of intrascrotal temperature in normal and subfertile men. J. Reprod. Fertil. 82:563-566.

WRIGLEY, E. A., and R. SCHOFIELD. 1981. The